Abstract: Method, system, and programs for determining a keyword from user agent strings are disclosed. In one example, a plurality of user agent strings is received. The plurality of user agent strings is grouped into one or more clusters. The one or more clusters comprise a first cluster that includes two or more user agent strings. The two or more user agent strings in the first cluster are compared. Based on the comparing, a keyword is determined from the first cluster. The keyword represents a type of user agent information.

Abstract: The present teaching relates to methods, systems, and programming for information retrieval. A search result associated with a search query is obtained and provided to a user. Upon receiving a filtering request from the user, the search result is filtered based on the filtering request to generate an updated search result. The updated search result is provided to the user in response to the filtering request.

Abstract: One or more computing devices, systems, and/or methods for monitoring levels of activity of client devices using a cluster of servers having a decentralized network architecture are provided, where over-counting, which may be caused by an uneven distribution of requests transmitted by the client devices to the cluster of servers, may be mitigated. For example, a request may be received by a first server, of the cluster of servers, from a client device. A first counter value associated with a level of activity of the client device may be incremented by a first number. One or more data packets may be transmitted to one or more servers of the cluster of servers. Each data packet of the one or more data packets may comprise an instruction to increment a counter value associated with the client device by a second number, which may be different than the first number.

Abstract: One or more computing devices, systems, and/or methods for presenting content of an application are provided. For example, a first content interface, associated with an application, may be displayed using a first device. First activity performed using the first content interface may be detected. The first activity may be analyzed to generate a first activity profile associated with the first content interface. A first request to access the application may be received from the first device. The first activity profile may be selected from a plurality of activity profiles associated with the user account, based upon a determination that the first request is associated with the first content interface. Content items of the content items database may be prioritized, based upon the first activity profile, to generate a list of content items associated with the first content interface. The list of content items may be displayed by the first device.

Abstract: The present teaching relates to a method, system, and programming for content personalization. A request is received from a user to obtain a content item. Information indicative of a literacy-level of the user is obtained and the content item to be provided to the user is retrieved. The content item is modified by updating information included in the content item based on the literacy-level of the user to generate an updated content item. The updated content item is provided to the user in response to the request.

Abstract: The present teaching relates to managing computing resources. In one example, information about resource utilization on a computing node is received from the computing node. Available resource on the computing node is determined based on the information. A model generated in accordance with reinforcement learning based on simulated training data is obtained. An adjusted available resource is generated based on the available resource and the model with respect to the computing node. The adjusted available resource is sent to a scheduler for scheduling one or more jobs to be executed on the computing node based on the adjusted available resource.

Abstract: One or more computing devices, systems, and/or methods for providing recommendations to travelers are provided. For example, locational data associated with a device of a user is evaluated to identify a set of location points at which the device was located over time. Location point pairings are generated from the set of location points, where a location point pairing may comprise a departure location point and an arrival location point. The location point pairings are filtered based upon various criteria to remove location point pairings that are not indicative of air flight travel (e.g., a location point pairing not satisfying an air flight speed threshold or an air flight travel distance threshold). The user may be determined as an air flight traveler that has recently used air flight travel to reach a destination location. A recommendation of content for the destination location is provided to the user.

Abstract: One or more computing devices, systems, and/or methods for automated materialized view table generation and maintenance are provided. A log, comprising queries and latencies of processing the queries, is evaluated to identify a list of combinations of fields that occur greater than a threshold frequency and/or occur in queries having latencies greater than a threshold latency. A materialized view generation script is executed against a main database to generate a materialized view table associated with a combination of one or more fields from the list. A middleware component is configured to selectively direct a query to the main database or to the materialized view table based upon whether the materialized view table comprises preliminary query results for fields specified by the query.

Abstract: Disclosed are embodiments for generating metadata files for composite datasets. In one embodiment, a method is disclosed comprising generating a tree representing a plurality of datasets; parsing the tree into an algebraic representation of the tree; identifying a plurality of terms in the algebraic representation, each term in the terms comprising at least two factors, each of the two factors associated with a dataset in the plurality of datasets; generating a metadata object of the plurality of terms; serializing the metadata object to generate serialized terms; and storing the serialized terms in a metadata file associated with the plurality of datasets.

Abstract: Methods, systems and programming for providing query suggestions based on user feedback. In one example, a prefix of a query is first received. An input including a prefix of a query is received from a user in a search session. A plurality of query suggestions are fetched based on the prefix of the query. Rankings of the plurality of query suggestions are determined based, at least in part, on the user's previous interactions in the search session with respect to at least one of the plurality of query suggestions. The at least one of the plurality of query suggestions has been previously provided to the user in the search session. The plurality of query suggestions are provided in the search session based on their rankings as a response to the input.

Abstract: Systems and methods are disclosed for utilizing sender-recipient pair data to establish sender-level trust in future communication. One method comprises receiving raw communication data over a network and testing the received raw communication data against trained machine learning data to predict whether the raw communication data is associated with expected communication data. The raw communication data is sorted for expected communication data, which is further analyzed for sender-recipient pair data and assigned an expected communication pair data score. Senders associated with an expected communication pair data score that meets or exceeds a threshold are labeled and stored in a database as trusted. As a result of the sender-recipient pair analysis, recipients at-risk for being scammed can be identified, senders misidentified as spammers can be properly classified, and machine learning techniques utilized for analyzing raw communication data can be fine-tuned.

Abstract: Systems and methods for securing digital content using hidden folders are disclosed. In one embodiment, a method comprises displaying an application, the application including a user interface for displaying digital content items and receiving input events; monitoring keystrokes entered by a user of the client device while the application is displayed; generating a candidate passcode based on the keystrokes; determining that the candidate passcode is a valid passcode has been entered when the candidate passcode is equal to a known passcode; transmitting a request for one or more hidden items from a server device, the request including the valid passcode; receiving the one or more hidden items; and updating the user interface to display the one or more hidden items.

Abstract: The present disclosure relates to computer systems implementing methods for online content recommendation.

Abstract: The present teaching relates to method and system for generating a stream of content items. A plurality of entities associated with a time-window are obtained, wherein each entity of the plurality of entities is associated with at least one content item. For each entity, a first parameter with respect to the time-window, a second parameter with respect to previous time-windows, and a trendiness score based on a function of the first parameter and the second parameter are respectively calculated. A graph based on one or more entity-pairs is generated, wherein each entity-pair of the one or more entity-pairs satisfies a first criterion. A stream of content items is generated based on the graph, wherein each content item in the stream of content items corresponds to at least one of the one or more entity pairs.

Abstract: Disclosed are systems and methods for automatically deleting messages from a recipient's inbox. The disclosed systems and methods provide the ability for automatic actions to be taken on delivered messages based on a passage of time. This enables a sender of messages, email service provider and/or email platform to exert control over sent messages to limit the number and type of operations that may be performed on such messages. For example, operations such as saving, forwarding, printing, copying, or otherwise duplicating the message and/or message data can be prohibited and all together rendered impossible. The disclosed systems and methods enables the purging of messages and associated message data from a recipient's inbox at a certain specified time, after the passage of a pre-determined amount of time, or upon the detection of a specified event.

Abstract: A method is provided, including: processing interactions by a plurality of users with a plurality of content items, the content items being provided over a network in response to user requests received over the network, wherein each content item is associated with one or more entities; for each user, determining a user entity set that includes entities associated with content items with which the user interacted; embedding the users and the entities in a vector space, wherein the embedding is configured to place a given user, and the entities of the given user's user entity set, in proximity to each other in the vector space; for each user, performing a proximity search in the vector space to identify a set of nearest entities to the user in the vector space; for each user, generating a user profile using the identified set of nearest entities to the user.

Abstract: A seemingly infinite and continuous stream of online content can be tracked by a movement tracker that can track an amount of movement of a stream of content. For example, such a movement tracker can track the amount of movement per session of a client-side application, such as per session of a web browser. In an example, the tracking of the movement can occur by tracking a measurable parameter of the stream that indicates the amount of movement, such as scroll distance. The movement tracker may also be configured to determine user interaction data according to the tracked amount of movement.

Abstract: The present teaching relates to method, system, and programming for responding to an image related query. Information related to each of a plurality of images is received, wherein the information represents concepts co-existing in the image. Visual semantics for each of the plurality of images are created based on the information related thereto. Representations of scenes of the plurality of images are obtained via machine learning, based on the visual semantics of the plurality of images, wherein the representations capture concepts associated with the scenes.

Abstract: One or more computing devices, systems, and/or methods are provided. Event information associated with a plurality of events may be identified. The plurality of events may be associated with client devices and entities. A network profile associated with the client devices and the entities may be generated based upon the event information. A similarity profile associated with the client devices may be generated based upon the network profile. The similarity profile may be indicative of one or more similarity scores associated with a first client device and one or more client devices. A user profile associated with the first client device may be modified, based upon the similarity profile and/or one or more user profiles associated with the one or more client devices, to generate a modified user profile. Content may be selected for presentation via the first client device based upon the modified user profile.

Abstract: Method, system, and programs for measuring user engagement with content items. In one example, a query is received. A set of content items related to the query is obtained. A presentation of at least one content item of the set of content items is provided on a user interface. A user activity related to the at least one content item is determined. An amount of time between a time at which the presentation of the at least one content item is provided on the user interface and a time at which the user activity occurred is determined. A score associated with the content item is determined based on the amount of time. Information related to user engagement with the set of content items is generated based on the score.