Abstract: Described herein is a conversation engine that can be used in a system such as a personal digital assistant or search engine that combines a dynamic knowledge graph built during execution of a request and one or more static knowledge graphs holding long term knowledge. The conversation engine comprises a state tracker that holds the dynamic knowledge graph representing the current state of the conversation, a policy engine that selects entities in the dynamic knowledge graph and executes actions provided by those entities to move the state of the conversation toward completion, and a knowledge graph search engine to search the static knowledge graph(s). The conversation is completed by building the dynamic knowledge graph over multiple rounds and chaining together operations that build toward completion of the conversation. Completion of the conversation results in completion of a request by a user.

Abstract: Systems and methods are disclosed for task identification and tracking using shared conversational context. In one implementation, a first communication from a first user is received within a communication session. The first communication is processed to identify a first content element within the first communication. A second communication is received within the communication session. The second communication is processed to identify a second content element within the second communication. The first content element is associated with the second content element. Based on an association between the first content element and the second content element, a task is identified. An action is initiated with respect to the task.

Abstract: Systems and methods are disclosed for personalized communications using semantic memory. In one implementation, a first communication is received from a user and processed to identify a first content element within the communication. The first content element is associated with a second content element within a content repository. A second communication that includes the first content element is received from the user. Based on an association between the first content element and the second content element within the content repository, a third communication that includes the second content element is generated and provided to the user in response to the second communication.

Abstract: A system and method for personalizing a user's digital assistant. The digital assistant is accessed via the user's device and the user initiates a query via the digital assistant. The digital assistant then performs a search to provide a response to the user's query. A session is defined and stored linking the user's query with the digital assistant's response. A knowledge base is generated with information associated with a plurality of sessions. A shadow profiled may also be generated from which inferences may be generated. Information associated with prior sessions may be retrieved in response to subsequent queries from the user.

Abstract: Conversational understanding systems allow users to conversationally interface with a computing device. In examples, a query may be received that includes a request for execution of a task. A data exchange task definition may be accessed. The data exchange task definition assists a conversational understanding system in managing task state tracking for information needed for task execution. Using the data exchange task definition, a per-turn policy for interacting with the user computing device is generated based on the state of a dialogue with a computing device and an evaluation of a process flow chart provided by a task owner resource. The task owner resource may be independent from the conversational understanding system. A response to the query may be generated and output based on the per-turn policy. In examples, the per-turn policy is used to generate one or more responses during a dialogue with a user via a computing device.

Abstract: Aspects herein provide third party application authors with a user interface authoring platform that automates and simplifies a task definition process while also providing the ability to leverage pre-existing language understanding models and canonicalization and resolution modules that are provided by the operating system on which the CU system resides or as provided by other third parties. In particular, the present disclosure provides a method and system for authoring a task using a user interface authoring platform.

Abstract: Architecture that utilizes server-based signals (e.g., past engagement, application popularity, spell-correction, mined search patterns, machine learning models, etc.) to improve relevance of search results for local applications and settings. The architecture works for any operating system (OS) and any client device that has local settings or applications installed. The architecture also covers instances where server-signals are being used to improve queries on devices where settings are searched but no applications are installed or will not be installed.

Abstract: Techniques are provided for the efficient location, processing, and retrieval of local product information derived from web pages generally locatable through form queries submitted to web pages often referred to as the “deep” or “hidden” web. In an embodiment, information such as product information and dealer-location information is located on a web page form such as a dealer-locator form. After location of a suitable web page form, editorial wrapping is performed to create an automated information extraction process. Using the automated information extractor, deep-web crawling is performed. A grid-based extraction of individual business records is performed, and matching and ingestion are performed in conjunction with a business listing database. Finally, metadata tags are added to entries in the business listing database. Metadata tags also may be added to entries in other databases.

Abstract: Methods and apparatus for performing computer-implemented extraction of temporal information for business entities and events are disclosed. In one embodiment, a sequence of text is obtained. A label is assigned to one or more of a plurality of segments of the text such that each of the one or more of the plurality of segments of the text is classified as temporal data in one of a plurality of classes of temporal data. One or more rules are applied to the one or more segments of the text that have been classified as temporal data to generate a structured representation of the temporal data, where the rules include one or more schematic rules. Each of the schematic rules pertains to one or more of the plurality of classes of temporal data and indicates a structure in which temporal data in the corresponding one or more of the plurality of classes is to be stored.

Abstract: Methods and apparatus for performing computer-implemented extraction of temporal information for business entities and events are disclosed. In one embodiment, a sequence of text is obtained. A label is assigned to one or more of a plurality of segments of the text such that each of the one or more of the plurality of segments of the text is classified as temporal data in one of a plurality of classes of temporal data. One or more rules are applied to the one or more segments of the text that have been classified as temporal data to generate a structured representation of the temporal data, where the rules include one or more schematic rules. Each of the schematic rules pertains to one or more of the plurality of classes of temporal data and indicates a structure in which temporal data in the corresponding one or more of the plurality of classes is to be stored.

Abstract: Techniques are provided for the efficient location, processing, and retrieval of local product information derived from web pages generally locatable through form queries submitted to web pages often referred to as the “deep” or “hidden” web. In an embodiment, information such as product information and dealer-location information is located on a web page form such as a dealer-locator form. After location of a suitable web page form, editorial wrapping is performed to create an automated information extraction process. Using the automated information extractor, deep-web crawling is performed. A grid-based extraction of individual business records is performed, and matching and ingestion are performed in conjunction with a business listing database. Finally, metadata tags are added to entries in the business listing database. Metadata tags also may be added to entries in other databases.