IMAGE APPENDED SEARCH STRING
Example embodiments of the present disclosure include a system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for providing an image appended search string. In example embodiments, a selection of an image is received. The image is a search result from a plurality of search results obtained based on a matching process performed on a current search string. A keyword corresponding to the selected image is determined. The keyword corresponding to the selected image is appended to the current search string. The plurality of search results is refined based on the appending of the keyword. The refined search results are then caused to be presented.
This application is a continuation of U.S. patent application Ser. No. 14/588,323, filed Dec. 31, 2014 (Attorney Docket No. IP-P2780US1/EBAY.281222), which is herein incorporated by reference in its entirety.
TECHNICAL FIELDThe present disclosure relates generally to data analysis and, in a specific example embodiment, to providing an image appended search string.
BACKGROUNDTypically, when a user performs a search, the user must manually enter a search string and then select an “enter” key. Once the “enter” key is selected, a search system takes the entire search string and performs a search for entries that match the entire search string.
Various ones of the appended drawings merely illustrate example embodiments of the present invention and cannot be considered as limiting its scope.
The description that follows includes systems, methods, techniques, instruction sequences, and computing machine program products that embody illustrative embodiments of the present invention. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide an understanding of various embodiments of the inventive subject matter. It will be evident, however, to those skilled in the art that embodiments of the inventive subject matter may be practiced without these specific details. In general, well-known instruction instances, protocols, structures, and techniques have not been shown in detail.
Example embodiments described herein provide systems and methods for providing dynamic search content to a user in an efficient and expedited manner. Example embodiments allow the user to enter a search string into a search bar comprising one or more keywords. As the user is entering (e.g., typing or speaking) the search string, the dynamic content delivery search system is already taking the keywords and preforming a matching process on-the-fly to determine matching results to the keywords. This is done without the user having to select an “enter” key, for example. As such, as soon as the user is done entering an entire search string, and without the user having to select the “enter” key, search results are queued up to be presented to the user, and may be automatically “surfaced” around the search bar.
In example embodiments, a selection of an image from the search results is received. A keyword corresponding to the selected image is determined. The keyword may be determined by accessing metadata (e.g., attributes describing an item in the image) corresponding to the selected image. A level corresponding to the search results is determined, whereby the keyword corresponding to the selected image is based on the level. In some cases, the image may be tagged (e.g., with an additional piece of metadata associated with the image) to indicate the level. The keyword corresponding to the selected image is appended to the current search string, and the search results are refined based on the appended keyword. The refined search results are then caused to be presented. Accordingly, a selection of a visual representation or image can be used to refine a search. This may be advantageous when the user, for example, does not know what a particular item is called, how to describe a particular item, or a name of a store or organization associated with a particular item. Instead, the user may refine a more generic search using images depicting items that are of interest to the user.
As a result, one or more of the methodologies described herein facilitate performing a search. Instead of the user repeatedly entering different search strings in an attempt to obtain a search result when the user is unsure of how to describe an item of interest, for example, the user can start with a more generic search and use images that help refine the search. Accordingly, less searching may be needed to obtain the desired search results. When these effects are considered in aggregate, one or more of the methodologies described herein may obviate a need for certain efforts or resources that otherwise would be involved in performing searches. Computing resources used by one or more machines, databases, or devices may be reduced. Examples of such computing resources include processor cycles, network traffic, memory usage, data storage capacity, power consumption, and cooling capacity.
With reference to
The client devices 110, 112 may each comprise a mobile phone, desktop computer, laptop, or any other communication device that a user may utilize to access the networked system 102. In some embodiments, each client device (e.g., client device 110) may comprise a display module (not shown) to display information (e.g., in the form of user interfaces). In further embodiments, the client device may comprise one or more of a touch screen, accelerometer, camera, microphone, and Global Positioning System (GPS) device. The client devices 110, 112 may be a device of a user, which is used to trigger processing of information, perform searches, and receive results from the dynamic content delivery search system provide by the networked system 102. In one embodiment, the networked system 102 includes or is linked to a network-based marketplace that manages digital goods, publishes publications comprising product listings of products available on the network-based marketplace, and manages payments for these marketplace transactions.
An Application Program Interface (API) server 114 and a web server 116 are coupled to, and provide programmatic and web interfaces respectively to, one or more application servers 118. The application server 118 hosts a publication system 120, which may comprise one or more modules, applications, or engines, and which may be embodied as hardware, software, firmware, or any combination thereof The application server 118 is, in turn, coupled to one or more database servers 122 facilitating access to one or more information storage repositories or databases 124. In one embodiment, the database 124 is a storage device that stores content (e.g., product listings, store information, advertisements, videos) that may be searched by the dynamic content delivery search system.
In example embodiments, the publication system 120 publishes content on a network (e.g., Internet). As such, the publication system 120 provides a number of publication functions and services to users that access the networked system 102. In example embodiments, the publication system 120 is a marketplace environment whereby a user may purchase products listed thereon. However, it is noted that the publication system 120 may, in alternative embodiments, be associated with a non-marketplace environment such as an informational (e.g., search engine) or social networking environment. The publication system 120 will be discussed in more detail in connection with
While the publication system 120 is shown in
Referring now to
The publication system 120 provides a number of publishing, listing, and price-setting mechanisms whereby a seller (e.g., individual, store, company) may list or publish information concerning) goods or services for sale, a buyer can express interest in or indicate a desire to purchase such goods or services, and a price can be set for a transaction pertaining to the goods or services. To this end, the publication system 120 may comprise at least one publication engine 202 and one or more auction engines 204 that support auction-format listing and price setting mechanisms (e.g., English, Dutch, Chinese, Double, Reverse auctions, etc.).
A store engine 206 allows a seller to group listings within a “virtual” store, which may be branded and otherwise personalized by and for the seller. Such a virtual store may also offer promotions, incentives, and features that are specific and personalized to the seller. In one example, the seller may offer a plurality of items as Buy-It-Now items in the virtual store, offer a plurality of items for sale or auction, or a combination of both. The seller may also offer other content via their store. For example, the seller may provide recipes or videos (e.g., showing how to make or use an item).
Navigation of the publication system 120 may be facilitated by a navigation engine 208. For example, a browse module (not shown) of the navigation engine 208 allows users to browse various search results, categories, catalogs, or inventory data structures according to which content may be classified within the publication system 120. Various other navigation applications within the navigation engine 208 may be provided to supplement the browsing applications.
In order to make content available via the networked system 102 as visually informing and attractive as possible, the publication system 120 may include an imaging engine 210 that enables users to upload images or videos for inclusion within publications and to incorporate images or videos within viewed publications. The imaging engine 210 may also receive image data from a user as a search query and utilize the image data (e.g., metadata) to identify an item depicted or described by the image data. In accordance with example embodiments, the imaging engine 210 may use images or other digital content obtained from third party media hosting sites.
A content creation engine 212 allows users (e.g., sellers) to conveniently author publications, content, or listings of items, In one embodiment, the content pertains to goods or services that a user (e.g., a seller) to transact via the publication system 120. In other embodiments, a user may create content that is an advertisement or other form of publication (e.g., tutorial video).
A content management engine 214 allows the users to manage such publications or content. Specifically, where a particular user has authored or published a large number of content, the management of such content may present a challenge. The content management engine 214 provides a number of features (e.g., auto-relisting, inventory level monitors, etc.) to assist the user in managing such content.
A search engine 216 performs searches for content in the networked system 102 that match a query, appends keywords to a search string, queues up search results, and manages presentation of the search results. The searches are performed on-the-fly as the user is entering the search string. The results may be queued up for presentation to the user (e.g. cached) as soon as the user has completed the search string and without the user having to select an “enter” button or key. The search engine 216 will be discussed in more detail in connection with
Although the various components of the publication system 120 have been defined in terms of a variety of individual modules and engines, a skilled artisan will recognize that many of the items can be combined or organized in other ways and that not all modules or engines need to be present or implemented in accordance with example embodiments. Furthermore, not all components of the publication system 120 have been included in
As is understood by skilled artisans in the relevant computer and Internet-related arts, each component (e.g., a module or engine) illustrated in
The query input module 302 manages operations involving input of a search string within a search box displayed on a user interface presented to a user. Accordingly, the query input module 302 detects when a search string is being entered into the search box and identifies one or more keywords of the search string. For example, as soon as a user enters a first keyword in the search, the query input module 302 detects the entry of the keyword string (e.g., detecting a space after a series of letters or detecting selection of a space bar), identifies the keyword, and passes the keyword to the match module 304. This process continues for each additional keyword of the search string. The query input module 302 also manages operations involving appending keywords to the search string based on a selection from a previously presented search result as will be discussed in more detail below.
The match module 304 performs a matching process to determine matches to one or more keywords of the search string in real-time. In example embodiments, the match module 304 receives a first keyword detected by the query input module 302 and performs a first matching process to derive results that match the first keyword. Subsequently, if the query input module 302 detects a second keyword in the search string, the match module 304 uses that second keyword to refine the matching results derived from the first keyword. This matching process continues until every keyword from the search string has been incorporated into the matching process. An end of the search string may be detected, for example, by a space or a pause in entry of any further keywords.
The results module 306 manages operations involving processing the search results prior to presenting the results to the user. In example embodiments, the results module 306 determines a level of a current or previous search and search results. Based on the level of the current or previous search or search result, different versions of content may be retrieved for presentation to the user. For example, if the level of the previous search results was at a category level (e.g., furniture), then a current search result building off of the previous search result (e.g., refining the previous search result) may be at a sub-category level (e.g., sofas). In further embodiments, the level of the current or previous search is provided to the query input module 302 in order for the query input module 302 to determine one or more keywords to append to a previous search string as will be discussed in more detail below.
The user interface module 308 manages operations for causing presentation of the search results to the user (e.g., on a display of a client device of the user). In example embodiment, the user interface module 308 causes the search results to be present in a graphical format on one or more sides of a search bar or box. Accordingly, the user interface module 308 accesses images for the search results, and sends instructions and data to the client device of the user (e.g., client device 110) to present such a user interface. The user interface module 308 also manages appending previous search results to an end of a current search result set so as not to require the user to back track (e.g., select a “back” button or reload a page with the previous search results).
The user interface 400 also provides a plurality of content shown as images from which the user may select to append to a present search string. The plurality of content may be personalized to the user in instances where the user is known to the publication system 120 (e.g., via a cookie, logged in with the publication system 120). For example, the content displayed on the home page may comprise categories of items that the user has previously purchased, has performed previously searches on, owns, has shown interest in, or any combination therein.
Referring now to
As shown in the example user interface of
The one or more keywords appended to the search string are dependent on a level of a current search. In one embodiment, each one of the displayed images is tagged (e.g., with metadata) to indicate a current level in the search. For example, returned results for “summer cocktail” represent categories (visual category representations). As such, the search engine 216 will detect that the image corresponding to “drinking glasses” has a tag of “category.” Therefore, a selection of “drinking glasses” from the category level will indicate to the search engine 216 to append a keyword that corresponds to the category level and return results in a sub-category (e.g., products, stores) corresponding to drinking glasses. As a further example, if the current level were the sub-category of drinking glasses, then selection of an image displaying drinking glasses causes a keyword that corresponds to a sub-category level to be appended and return results at an item level (e.g., individual items available for purchase).
As shown in
Additionally, an image 406 corresponding to a video 408 related to drinking glasses is displayed in
A further selection of the image 406 (or the now playing video 408) results, for example, in a full screen 410 of the video 408 being displayed as shown in
Additionally, one or more keywords linked to the selected image 406 are appended in the search bar 402. In the present example, “from Brooklyn Glass & Mercantile Co.” is appended to “summer cocktail glasses.” The appending of the keywords associated with Brooklyn Glass & Mercantile Company causes the search engine 216 to further refine previous search results even though the user has not requested a further refinement (e.g., the user only indicated to play the video). As a result, the further refined search results may be queued up and ready for presentation prior to the user indicating a desire for more refined search results associated with the Brooklyn Glass & Mercantile Company.
Upon a further selection of the video 408 (or image corresponding to the video 408), the further refined search results are presented (e.g., items related to summer cocktail glasses from the Brooklyn Glass & Mercantile Company) as shown in
The user may scroll through the further refined search results. For example, if the display is on a touch screen device (e.g., a tablet), the user can swipe in an upward motion to scroll the further refined search results upward. At the end of the further refined search results, previous search results from a level above continue to be shown. As such, as the user continues to scroll up, the refined results from the Brooklyn Glass & Mercantile Company will push off of the user interface and the search results based on the search string “summer cocktail glasses” is presented as part of a continuously scrolling user interface as shown in
In operation 504, a keyword of the search string is identified. In example embodiments, the query input module 302 identifies each keyword as it is being entered in the search bar. For example, as soon as a user enters a first keyword in the search string, the query input module 302 detects and identifies the first keyword (e.g., “summer”). In one embodiment, the query input module 302 detects completion of entry of the first keyword based on a space after the keyword.
The keyword is then passed to the match module 304 where, in operation 506, matches to the keyword are determined in real-time. In example embodiments, the match module 304 receives the keyword detected by the query input module 302 and performs a matching process to derive results that match the keyword. As a result, matching results that match the keyword are determined and ready to be presented to the user (e.g., queued up for delivery).
In operation 508, a determination is made as to whether there is a next keyword in the search string. For example, the query input module 302 determines whether a next or subsequent keyword is entered for the search string. If a next keyword is detected, the method returns to operation 504 whereby the next keyword (e.g., “cocktail”) is identified and used, in operation 506, to refine the previous matching results based on the first keyword.
This matching process continues until every keyword from the search string has been incorporated into the matching process. The addition of each keyword refines the previous matching results. As such, the matching process becomes significantly faster and requires less processing power with each iteration since the next keyword matches a smatter set of previous matching results.
Once no further keywords are detected (e.g., entry of the search string is completed), images of the final matches of the search results are accessed in operation 510. Accordingly, the user interface module 308 accesses the images from a database or repository storing publication information (e.g., database 124). The images may comprise images from third parties or stores, images from a catalog, images uploaded by various entities via the imaging engine 210, or any combination of these.
In operation 512, the search results are caused to be displayed on the client device (e.g., the client device 110) of the user. In example embodiments, the user interface module 308 sends instructions and data (e.g., image data) to the client device of the user to present a user interface whereby the images of the search results are displayed (e.g., above, below, or around the search bar). It is noted that while images providing a visual representation of the search results is discussed as being displayed as the search results, alternative embodiments may present other forms of search results. For example, the search results may be provides in a list format (with or without an associated image).
Referring now to
In operation 602, a selection of one of the images is received. In example embodiments, the input query module 302 receives the selection of the image and accesses metadata associated with the selected image.
In operation 604, a level of the current search and the selected image is determined. For example, a determination may be made as to whether the selected image is a broad category image or if the selected image is a specific item image. The one or more keywords to be appended to the search string or the search results to be returned are dependent on a level of the current search. In one embodiment, the selected image is tagged to indicate a current level in the search (e.g., category level, sub-category level) when it is caused to be displayed to the user. In this embodiment, the level of the search is determined from the tag.
In operation 606, the one or more keywords are determined and appended to the search string. The one or more keywords may be determined from the metadata associated with the selected image based on the current level of the search. For example, if the current level of the search presents (category) results for “summer cocktail” and the user selects an image corresponding to Pottery Barn cocktail glasses, the keyword to be appended is “glasses.” However, if the current level of the search presents (sub-category) results for “summer cocktail glasses” and the same image corresponding to Pottery Barn cocktail glasses is selected, then the keyword to be append may be “Pottery Barn” resulting in a search string “summer cocktail glasses from Pottery Barn.” In yet a further example, if the current level of the search presents a storefront for Pottery Barn based on the search string “summer cocktail glasses from Pottery Barn,” and the user select the same image, then the type of glass depicted in the image from Pottery Barn may be appended (e.g., “classic margarita”). In example embodiments, the user interface module 308 causes the one or more keywords to be added to the search string displayed in the search bar. The input query module 302 also provides the one or more keywords to the match module 304.
In operation 608, the match module 304 determines matches for the appended search string. Accordingly, the previous search results are refined by the appended keyword(s) to obtain a refined search result that is a search level lower than the previous search. The refining of the previous search results using the appended keyword(s) is performed without the user doing anything more than selecting the image (e.g., no “enter” key is required).
In operation 610, images of the final matches of the search results are accessed. Accordingly, the user interface module 308 accesses the images from a database or repository storing publication information (e.g., database 124). The images may comprise images from third parties or stores, images from a catalog, images uploaded by various entities via the imaging engine 210, or any combination of these.
In operation 612, the search results are caused to be displayed on the user device of the user. In example embodiments, the user interface module 308 sends instructions and data (e.g., image data) to the client device of the user to present a user interface whereby the images of the search results are displayed (e.g., above, below, or surrounding the search bar).
In operation 702, a current level of search results is caused to be presented on a user device (e.g., search results for “summer cocktail glasses from the Brooklyn Glass & Mercantile Co.”). In example embodiment, the user interface module 308 causes the search results to be present in a graphical format by sending instructions and data to the client device of the user to present such a scrollable user interface. The search results may include text, images, or a combination of both for each result. The method 700 assumes that at least one initial search and a refinement of the initial search has been performed, and that the current level of the search result being caused to be presented is the search results based on the refinement.
In operation 704, a scroll indication is detected. For example, the user may swipe upward on a touchscreen displaying the current level of the search results. In response, the user interface module 308 causes the search results to scroll in the direction of the scroll indication in operation 706.
In operation 708, a determination is made as to whether an end of the search results in the current level (e.g., search results for “summer cocktail glasses from the Brooklyn Glass & Mercantile Co.”) is reached. If the end of the search result in the current level is not reached, then the user interface continues to monitor for a scroll indication and causes presentation of scrolling search results in the direction of the scroll indication.
However, if the end of the search results in the current level is reached, then the user interface module 308 appends search results from a previous level (e.g., search results for “summer cocktail glasses”) to a bottom or end of the search results in the current level. Accordingly, the search engine 216 understands the relationships between all of the items in the search results of the current level with respect to the overall total search result. If the search results of the current level (e.g., sports-sports categories—baseball) reaches an end, the user interface module 308 returns the search results to the previous level (e.g., sports-sport categories).
The appending of the previous search results does not need to serve a new page in order to present the previous search results. Instead, the previous search results are retrieved from cache and added to the end of the current search results, thus leveraging a cached experience and reducing processing requirements.
In alternative embodiments, the machine 800 operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine 800 may operate in the capacity of a server machine or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine 800 may be a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a personal digital assistant (PDA), a cellular telephone, a smartphone, a web appliance, a network router, a network switch, a network bridge, or any machine capable of executing the instructions 824, sequentially or otherwise, that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include a collection of machines that individually or jointly execute the instructions 824 to perform any one or more of the methodologies discussed herein.
The machine 800 includes a processor 802 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (IMP), an application specific integrated circuit (ASIC), radio-frequency integrated circuit (RFIC), or any suitable combination thereof), a main memory 804, and a static memory 806, which are configured to communicate with each other via a bus 808. The processor 802 may contain microcircuits that are configurable, temporarily or permanently, by some or all of the instructions 824 such that the processor 802 is configurable to perform any one or more of the methodologies described herein, in whole or in part. For example, a set of one or more microcircuits of the processor 802 may be configurable to execute one or more modules (e.g., software modules) described herein.
The machine 800 may further include a graphics display 810 (e.g., a plasma display panel (PDP), a light emitting diode (LED) display, a liquid crystal display (LCD), a projector, a cathode ray tube (CRT), or any other display capable of displaying graphics or video). The machine 800 may also include an alphanumeric input device 812 (e.g., a keyboard or keypad), a cursor control device 814 (e.g., a mouse, a touchpad, a trackball, a joystick, a motion sensor, an eye tracking device, or other pointing instrument), a storage unit 816, a signal generation device 818 (e.g., a sound card, an amplifier, a speaker, a headphone jack, or any suitable combination thereof), and a network interface device 820.
The storage unit 816 includes the machine-readable medium 822 (e.g., a tangible and non-transitory machine-readable storage medium) on which are stored the instructions 824 embodying any one or more of the methodologies or functions described herein. The instructions 824 may also reside, completely or at least partially, within the main memory 804, within the processor 802 (e.g., within the processor's cache memory), or both, before or during execution thereof by the machine 800. Accordingly, the main memory 804 and the processor 802 may be considered machine-readable media e.g., tangible and non-transitory machine-readable media).
In some example embodiments, the machine 800 may be a portable computing device, such as a smart phone or tablet computer, and have one or more additional input components (e.g., sensors or gauges). Examples of such input components include an image input component (e.g., one or more cameras), an audio input component (e.g., a microphone), a direction input component (e.g., a compass), a location input component (e.g., a global positioning system (GPS) receiver), an orientation component(e.g., a gyroscope), a motion detection component (e.g., one or more accelerometers), an altitude detection component (e.g., an altimeter), and a gas detection component (e.g., a gas sensor). Inputs harvested by any one or more of these input components may be accessible and available for use by any of the modules described herein.
As used herein, the term “memory” refers to a machine-readable medium able to store data temporarily or permanently and may be taken to include, but not be limited to, random-access memory (RAM), read-only memory (ROM), buffer memory, flash memory, and cache memory. While the machine-readable medium 822 is shown in an example embodiment to be a single medium, the term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) able to store instructions. The term “machine-readable medium” shall also be taken to include any medium, or combination of multiple media, that is capable of storing instructions for execution by a machine(e.g., machine 800), such that the instructions, when executed by one or more processors of the machine (e.g., processor 802), cause the machine to perform any one or more of the methodologies described herein. Accordingly, a “machine-readable medium” refers to a single storage apparatus or device, as well as “cloud-based” storage systems or storage networks that include multiple storage apparatus or devices. The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, one or more data repositories in the form of a solid-state memory, an optical medium, a magnetic medium, or any suitable combination thereof.
Furthermore, the tangible machine-readable medium is non-transitory in that it does not embody a propagating signal. However, labeling the tangible machine-readable medium as “non-transitory” should not be construed to mean that the medium is incapable of movement—the medium should be considered as being transportable from one physical location to another. Additionally, since the machine-readable medium is tangible, the medium may be considered to be a machine-readable device.
The instructions 824 may further be transmitted or received over a communications network 826 using a transmission medium via the network interface device 820 and utilizing any one of a number of well-known transfer protocols (e.g., HTTP). Examples of communication networks include a local area network (LAN), a wide area network (WAN), the Internet, mobile telephone networks, plain old telephone service (POTS) networks, and wireless data networks (e.g., Wifi, LTE, and WiMAX networks). The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding, or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible medium to facilitate communication of such software.
Throughout this specification, plural instances may implement components, operations, or structures described as a single instance. Although individual operations of one or more methods are illustrated and described as separate operations, one or more of the individual operations may be performed concurrently, and nothing requires that the operations be performed in the order illustrated. Structures and functionality presented as separate components in example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter herein.
Certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code embodied on a machine-readable medium or in a transmission signal) or hardware modules. A “hardware module” is a tangible unit capable of performing certain operations and may be configured or arranged in a certain physical manner. In various example embodiments, one or more computer systems (e.g., a standalone computer system, a client computer system, or a server computer system) or one or more hardware modules of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware module that operates to perform certain operations as described herein.
In some embodiments, a hardware module may be implemented mechanically, electronically, or any suitable combination thereof. For example, a hardware module may include dedicated circuitry or logic that is permanently configured to perform certain operations. For example, a hardware module may be a special-purpose processor, such as a field-programmable gate array (FPGA) or an ASIC. A hardware module may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware module may include software encompassed. within a general-purpose processor or other programmable processor. It will be appreciated that the decision to implement a hardware module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations.
Accordingly, the phrase “hardware module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. As used herein, “hardware-implemented module” refers to a hardware module. Considering embodiments in which hardware modules are temporarily configured (e.g., programmed), each of the hardware modules need not be configured or instantiated at any one instance in time. For example, where a hardware module comprises a general-purpose processor configured by software to become a special-purpose processor, the general-purpose processor may be configured as respectively different special-purpose processors (e.g., comprising different hardware modules) at different times. Software may accordingly configure a processor, for example, to constitute a particular hardware module at one instance of time and to constitute a different hardware module at a different instance of time.
Hardware modules can provide information to, and receive information from, other hardware modules. Accordingly, the described hardware modules may be regarded as being communicatively coupled. Where multiple hardware modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) between or among two or more of the hardware modules. In embodiments in which multiple hardware modules are configured or instantiated at different times, communications between such hardware modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware modules have access. For example, one hardware module may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information).
The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions described herein. As used herein, “processor-implemented module” refers to a hardware module implemented using one or more processors.
Similarly, the methods described herein may be at least partially processor-implemented, a processor being an example of hardware. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented modules. Moreover, the one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS), For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), with these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., an application program interface (API)).
The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the one or more processors or processor-implemented modules may be located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the one or more processors or processor-implemented modules may be distributed across a number of geographic locations.
Some portions of the subject matter discussed herein may be presented in terms of algorithms or symbolic representations of operations on data stored as bits or binary digital signals within a machine memory (e.g., a computer memory). Such algorithms or symbolic representations are examples of techniques used by those of ordinary skill in the data processing arts to convey the substance of their work to others skilled in the art. As used herein, an “algorithm” is a self-consistent sequence of operations or similar processing leading to a desired result, In this context, algorithms and operations involve physical manipulation of physical quantities. Typically, but not necessarily, such quantities may take the form of electrical, magnetic, or optical signals capable of being stored, accessed, transferred, combined, compared, or otherwise manipulated by a machine. It is convenient at times, principally for reasons of common usage, to refer to such signals using words such as “data,” “content,” “bits,” “values,” “elements,” “symbols,” “characters,” “terms,” “numbers,” “numerals,” or the like. These words, however, are merely convenient labels and are to be associated with appropriate physical quantities.
Unless specifically stated otherwise, discussions herein using words such as “processing,” “computing,” “calculating,” “determining,” “presenting,” “displaying,” or the like may refer to actions or processes of a machine (e.g., a computer) that manipulates or transforms data represented as physical (e.g., electronic, magnetic, or optical) quantities within one or more memories (e.g., volatile memory, non-volatile memory, or any suitable combination thereof), registers, or other machine components that receive, store, transmit, or display information. Furthermore, unless specifically stated otherwise, the terms “a” or “an” are herein used, as is common in patent documents, to include one or more than one instance. Finally, as used herein, the conjunction “or” refers to anon-exclusive “or,” unless specifically stated otherwise.
Although an overview of the inventive subject matter has been described with reference to specific example embodiments, various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of embodiments of the present invention. Such embodiments of the inventive subject matter may be referred to herein, individually or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is, in fact, disclosed.
The embodiments illustrated herein are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed. Other embodiments may be used and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. The Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled.
As used herein, the term “or” may be construed in either an inclusive or exclusive sense. Moreover, plural instances may be provided for resources, operations, or structures described herein as a single instance. Additionally, boundaries between various resources, operations, modules, engines, and data stores are somewhat arbitrary, and particular operations are illustrated in a context of specific illustrative configurations. Other allocations of functionality are envisioned and may fall within a scope of various embodiments of the present invention. In general, structures and functionality presented as separate resources in the example configurations may be implemented as a combined structure or resource. Similarly, structures and functionality presented as a single resource may be implemented as separate resources. These and other variations, modifications, additions, and improvements fall within a scope of embodiments of the present invention as represented by the appended claims. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.
Claims
1. A machine-readable medium storing instructions that, when executed by at least one processor of a machine, cause the machine to perform operations comprising:
- receiving a selection of an image, the image being a search result from a plurality of search results obtained from a matching process performed on a current search string entered in a search field;
- in response to receiving the selection of the image from the plurality of images, determining a keyword corresponding to the selected image;
- appending the keyword determined based on the selected image to the current search string in the search field;
- refining the search results based on appending the keyword to the search string in the search field;
- accessing images that correspond to the refined search results; and
- causing presentation of the images that correspond to the refined search results.
2. The machine-readable medium of claim 1, wherein determining the keyword corresponding to the selected image comprises:
- accessing metadata corresponding to the selected image; and
- deriving the keyword from the metadata.
3. The machine-readable medium of claim 1, wherein appending the keyword to the current search string comprises displaying the keyword appended to the current search string in the search field.
4. The machine-readable medium of claim 1, wherein refining the search results based on appending the keyword comprises searching for matches in the search results that include the keyword.
5. The machine-readable medium of claim 1, wherein refining the search results and causing the presentation of the images that correspond to the refined search results occurs without a user selecting an enter key.
6. The machine-readable medium of claim 5, wherein refining the search results and causing the presentation of the images that correspond to the refined search results occurs upon the user selecting a space key.
7. The machine-readable medium of claim 1, wherein the selected image is a still frame representation of a video.
8. A computer-implemented method comprising:
- receiving a selection of an image, the image being a search result from a plurality of search results obtained from a matching process performed on a current search string entered in a search field;
- in response to receiving the selection of the image from the plurality of images, determining a keyword corresponding to the selected image;
- appending the keyword determined based on the selected image to the current search string in the search field;
- refining the search results based on appending the keyword to the search string in the search field;
- accessing images that correspond to the refined search results; and
- causing presentation of the images that correspond to the refined search results.
9. The computer-implemented method of claim 8, wherein determining the keyword corresponding to the selected image comprises:
- accessing metadata corresponding to the selected image; and
- deriving the keyword from the metadata.
10. The computer-implemented method of claim 8, wherein appending the keyword to the current search string comprises displaying the keyword appended to the current search string in the search field.
11. The computer-implemented method of claim 8, wherein refining the search results based on appending the keyword comprises searching for matches in the search results that include the keyword.
12. The computer-implemented method of claim 8, wherein refining the search results and causing the presentation of the images that correspond to the refined search results occurs without a user selecting an enter key.
13. The computer-implemented method of claim 8, wherein refining the search results and causing the presentation of the images that correspond to the refined search results occurs upon the user selecting a space key.
14. The computer-implemented method of claim 8, wherein the selected image is a still frame representation of a video.
15. A computer system comprising:
- one or more processors; and
- a machine-readable medium storing computer useable instructions that, when used by the one or more processors, cause the one or more processors to:
- receive a selection of an image, the image being a search result from a plurality of search results obtained from a matching process performed on a current search string entered in a search field;
- in response to receiving the selection of the image from the plurality of images, determine a keyword corresponding to the selected image;
- append the keyword determined based on the selected image to the current search string in the search field;
- refine the search results based on appending the keyword to the search string in the search field;
- access images that correspond to the refined search results; and
- cause presentation of the images that correspond to the refined search results.
16. The computer system of claim 15, wherein determining the keyword corresponding to the selected image comprises:
- accessing metadata corresponding to the selected image; and
- deriving the keyword from the metadata.
17. The computer system of claim 15, wherein appending the keyword to the current search string comprises displaying the keyword appended to the current search string in the search field.
18. The computer system of claim 15, wherein refining the search results based on appending the keyword comprises searching for matches in the search results that include the keyword.
19. The computer system of claim 15, wherein refining the search results and causing the presentation of the images that correspond to the refined search results occurs without a user selecting an enter key.
20. The computer system of claim 15, wherein refining the search results and causing the presentation of the images that correspond to the refined search results occurs upon the user selecting a space key.
Type: Application
Filed: Dec 19, 2017
Publication Date: Apr 19, 2018
Inventors: Michael George Lenahan (Moraga, CA), Ben Mitchell (Oakland, CA), R. J. Pittman (San Jose, CA), Dave Lippman (San Jose, CA)
Application Number: 15/847,414