Abstract: The present disclosure relates generally to terpene glycosides, such as certain such compounds extracted from Stevia rebaudiana Bertoni, Rubus suavissimus, or Siraitia grosvenorii. The disclosure also provides for the use of such compounds as food ingredients, flavors, and sweeteners, and related methods. The disclosure also provides ingestible compositions comprising such compounds, as well as processes for extracting such compounds selectively from certain plant sources.

Abstract: Described herein are an extract from lettuce (Lactuca sativa), in particular of stalk lettuce (Lactuca sativa var. angustana), including 2-acetyl-1-pyrroline and, optionally, precursors of 2-acetyl-1-pyrroline as well as flavoring compositions including such an extract and a method for the preparation of such an extract. Also described herein are the use of such an extract as a taste or flavor ingredient in a consumer product and a method of enhancing, improving, modifying the taste or flavor of a consumer product by making use of such an extract.

Abstract: The present disclosure relates generally to terpene glycosides, such as certain such compounds extracted from Stevia rebaudiana Bertoni, Rubus suavissimus, or Siraitia grosvenorii. The disclosure also provides for the use of such compounds as food ingredients, flavors, and sweeteners, and related methods. The disclosure also provides ingestible compositions comprising such compounds, as well as processes for extracting such compounds selectively from certain plant sources.

Abstract: A system for training and deploying an artificial conversational entity using an artificial intelligence (AI) based communications system is disclosed. The system may comprise a memory storing machine readable instructions. The system may also comprise a processor to execute the machine readable instructions to receive a request via an artificial conversational entity. The processor may also transmit a response to the request based on a dialog tree generated from at least a model-based action generator and a memory-based action generator. The processor may further provide a training option to a user in the event the response is suboptimal. The processor may additionally receive a selection from the user via the training option. The selection may be associated with an optimal response.

Abstract: Systems and devices to perform knowledge-driven dynamic conversations and select content within automated agents such as chatbots and virtual assistants are disclosed. In an example, operations to facilitate a knowledge-based conversation session with a human user using an automated agent include: receiving a conversational input regarding a support issue; analyzing the conversational input to determine an intent and applicable entity properties associated with the intent; performing a multi-turn conversation to identify a solution using the intent and the applicable entity properties, by exchanging iterative questions and answers between the automated agent and the user to dynamically recalculate applicability of the solution to the support issue; and outputting information associated with the identified solution.

Abstract: Technologies described herein relate to receiving data from a social networking application, wherein the data is generated by a first individual, and executing an entity extraction algorithm to extract at least one entity from the received data. A hyperlink is displayed on a computing device utilized by a second individual, wherein the hyperlink is based at least in part upon the at least one entity, and the hyperlink is configured to direct the first individual to a search engine and is further configured to cause the search engine to execute a search that pertains to the at least one entity.

Abstract: A system for training and deploying an artificial conversational entity using an artificial intelligence (AI) based communications system is disclosed. The system may comprise a memory storing machine readable instructions. The system may also comprise a processor to execute the machine readable instructions to receive a request via an artificial conversational entity. The processor may also transmit a response to the request based on a dialog tree generated from at least a model-based action generator and a memory-based action generator. The processor may further provide a training option to a user in the event the response is suboptimal. The processor may additionally receive a selection from the user via the training option. The selection may be associated with an optimal response.

Abstract: Systems and devices to perform content authoring and establish conversation models for automated agents such as chatbots and virtual assistants are disclosed. In an example, operations for content authoring, to produce a conversation model, include: identifying respective intents from conversation segments in an unstructured data source; generating a knowledge graph of the conversation model to organize the identified intents; linking the intents in the knowledge graph to properties of the respective conversations, for properties used to guide a subject conversation with the conversation model; and outputting the conversation model, to be usable with the automated agent to conduct the subject conversation with a human user.

Abstract: Systems and devices to perform knowledge-driven dynamic conversations and select content within automated agents such as chatbots and virtual assistants are disclosed. In an example, operations to facilitate a knowledge-based conversation session with a human user using an automated agent include: receiving a conversational input regarding a support issue; analyzing the conversational input to determine an intent and applicable entity properties associated with the intent; performing a multi-turn conversation to identify a solution using the intent and the applicable entity properties, by exchanging iterative questions and answers between the automated agent and the user to dynamically recalculate applicability of the solution to the support issue; and outputting information associated with the identified solution.

Abstract: Various technologies pertaining to exploratory suggestions are described herein. A computer-implemented graph is constructed, where the graph includes nodes that are representative of aspects and edges that are representative of associations between aspects. An aspect is representative of a sub-topic of a topic or a sub-task of a task. The computer-implemented graph is learned based upon content of search logs, and is used to output exploratory suggestions, where a user is exploring a topic or attempting to complete a multi-step task.

Abstract: A system is described herein that includes a preference deriver component that receives a predefined preference rule that indicates a hierarchy pertaining to entities belonging to a domain, wherein each of the entities has attributes and values for such attributes corresponding thereto, and wherein the preference deriver component outputs preferences between various subsets of entities based at least in part upon the preference rule. The system also includes a learning component that learns a computer-implemented ranker component that is configured to rank the entities belonging to the domain, wherein the learning component learns the computer-implemented ranker based at least in part upon the preferences between the various subsets of the entities output by the preference deriver component.

Abstract: An electronic device including a casing, a printed circuit board, a contact spring and a connector is provided. The printed circuit board is disposed in the casing, and the contact spring is electrically connected to and located on the printed circuit board. The connector is movably disposed at the casing, and a part of the connector is protruded from the casing. While the connector is pressed by external force, the connector is moved to contact the contact spring so as to conduct with the printed circuit board.

Abstract: Technologies pertaining to automatically identifying sets of query attribute values that are highly correlative with user dissatisfaction with a search engine are described. Dissatisfied queries are automatically identified through analysis of search logs, wherein a dissatisfied query is a query submitted to a search engine by a user, wherein the user was dissatisfied with search results provided by the search engine responsive to receipt of the query. Sets of query attribute values that are highly correlated with dissatisfied queries, and thus user dissatisfaction, are automatically identified based at least in part upon the identifying of the dissatisfied queries. Subsequent to identifying a set of query attribute values, a segment-specific ranker is learned that is configured to rank search results responsive to receipt of a query with the set of query attribute values, wherein the segment-specific ranker outperforms a general purpose ranker for queries having the set of query attribute values.

Abstract: The assistive hearing device implementations described herein assist hearing impaired users of the device by using automated speech transcription to generate text representing speech received in audio signals which can then be read in a synthesized voice tailored to overcome a user's hearing deficiencies. A speech recognition engine recognizes speech in received audio and converts the speech of the received audio to text. Once the speech is converted to text, a text-to-speech engine can convert the text to synthesized speech that can be enhanced and output in a voice that compensates for the hearing loss profiles of a user of the assistive hearing device. By transcribing received speech into text the assistive hearing device implementations described herein eliminate background noise from the audio signal. By converting the transcribed text into a synthesized voice that is easier to understand to hearing impaired persons, their hearing deficiencies can be remedied.

Abstract: A network can be explored to investigate exploitive behavior. For example, network sites may be actively explored by a honey monkey system to detect if they are capable of accomplishing exploits, including browser-based exploits, on a machine. Also, the accomplishment of exploits may be detected by tracing events occurring on a machine after visiting a network site and analyzing the traced events for illicit behavior. Alternatively, site redirections between and among uniform resource locators (URLs) may be explored to discover relationships between sites that are visited.

Abstract: The claimed subject matter provides a system or method for web crawling hidden files. An exemplary method comprises loading a web page with a browser agent, and executing any dynamic elements hosted on the web page using the browser agent to insert pre-determined values. A list of form controls may be retrieved from the web page using the browser agent, and the controls may be analyzed using a driver component. Form control values may be sent from the driver component to the browser agent, and an event may be submitted to the web page by the browser agent or scripted content may be run to trigger operations on the web page corresponding to the form control values. A URL may be generated for various form control values using a generalizer.

Abstract: The claimed subject matter provides a system or method for web crawling hidden files. An example method includes loading a web page with a browser agent, and executing any dynamic elements hosted on the web page using the browser agent to insert pre-determined values. A list of form controls may be retrieved from the web page using the browser agent, and the controls may be analyzed using a driver component. Form control values may be sent from the driver component to the browser agent, and an event may be submitted to the web page by the browser agent or scripted content may be run to trigger operations on the web page corresponding to the form control values. A URL may be generated for various form control values using a generalizer.

Abstract: A crowdsourcing data structuring system and method for capturing unstructured data from the Web and adding structure by placing the data in a document that is accessible by others in a cloud computing environment. Using crowdsourcing, the unstructured data is annotated, amended, and verified to add structure to the unstructured data. An anchor and update module convert the data to a pointer that links the document to the data at an information source and stores the pointer in the document rather than the data itself. The data displayed in the document is updated whenever the information source is updated. A contribution module allows users to add data to the document, a validation module allows users to determine the validity of the data linked to in the document, and an expert ranking module allows users to rank the expert or contributor of the data in the document.

Abstract: Embodiments of automated cloud service performance prediction are disclosed. The automated cloud service performance prediction includes extracting one or more dependency relationships for each web object in the webpage. The prediction further includes determining an original performance metric value and original timing information associated with a page loading of a webpage. The prediction also includes simulating a page loading of the webpage based on the adjusted timing information and the dependency relationships to estimate a new performance metric value associated with the simulated page loading of the webpage. The prediction additionally includes comparing the original performance metric value to the new performance metric value to determine whether the adjusted timing information increased or decreased the new performance metric value relative to the original performance metric value.

Abstract: An exemplary system for monitoring search spam and protecting against search spam includes a self-monitoring subsystem to uncover spam patterns and a self-protection subsystem to protect against spam by providing spam-related information to strengthen a relevance ranking algorithm. An exemplary architecture for monitoring search spam includes a first component to receive one or more spammer targeted keywords and to search, scan and analyze URLs based at least in part on the one or more spammer targeted keywords, a second component to receive one or more URLs from the first component and to verify one or more of these URLs as a spam URL and a third component to collect spammer targeted keywords associated with one or more spam URLs and to provide one or more of the spammer targeted keywords to the first component.