Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for analyzing messages associated with an inbox of a user, and providing functionality to the inbox for alerting the user to specific forms of content included within each message. Such functionality can include displaying messages and/or the content contained therein in a novel, dedicated and modified and/or embedded portion of a message inbox. The messages can also be modified upon display within in the inbox to indicate that the message includes content of a specific type. Also, messages that include specific content types can also trigger the disclosed framework to generate and provide alerts to the user indicating the inbox has received or includes specific forms of such content.

Abstract: The present teaching relates to entity extraction and disambiguation. In one example, an entity name extracted from a data source associated with a user is obtained. One or more entity types associated with the entity name are determined. One or more entity candidates are identified with respect to each of the one or more entity types. An entity candidate is selected with respect to one of the one or more entity types to be an individual associated with the entity name.

Abstract: The present teaching relates to entity extraction and disambiguation. In one example, an entity name extracted from a data source associated with a user is obtained. One or more entity types associated with the entity name are determined. One or more entity candidates are identified with respect to each of the one or more entity types. An entity candidate is selected with respect to one of the one or more entity types to be an individual associated with the entity name.

Abstract: The present teaching relates to online task exchange. In one example, information related to a task automatically created based on an intent of a person is received. The task is posted to a plurality of parties that are capable of completing the task. One or more bids are received from at least some of the plurality of parties. At least one winning bid is selected from the one or more bids based on at least one criterion. Information indicative of a status as to completion of the task is received. Resource is allocated to the at least one winning bid based on the status.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for analyzing messages associated with an inbox of a user, and providing functionality to the inbox for alerting the user to specific forms of content included within each message. Such functionality can include displaying messages and/or the content contained therein in a novel, dedicated and modified and/or embedded portion of a message inbox. The messages can also be modified upon display within in the inbox to indicate that the message includes content of a specific type. Also, messages that include specific content types can also trigger the disclosed framework to generate and provide alerts to the user indicating the inbox has received or includes specific forms of such content.

Abstract: A first cluster of web objects is identified from a click-through data structure. The click-through data structure can organize web objects into clusters based on query results of web objects selected by a user. Also, a second cluster of web objects can be identified from a metadata data structure. The metadata data structure can organize web objects into clusters based on metadata associated with the web objects. An output set of web objects is selected, in real time, from the identifier clusters.

Abstract: The present teaching relates to automatically generating and completing a task. In one example, an input related to a person is received. An intent associated with the input is obtained. A task is automatically generated based on the input and the intent. In another example, a task automatically created based on an intent of a person is received. A task action list is obtained from the task. The task action list includes at least one action to be performed. Each of the at least one action is performed in accordance with the intent of the person.

Abstract: The present teaching relates to entity extraction and disambiguation. In one example, an entity name extracted from a data source associated with a user is obtained. One or more entity types associated with the entity name are determined. One or more entity candidates are identified with respect to each of the one or more entity types. An entity candidate is selected with respect to one of the one or more entity types to be an individual associated with the entity name.

Abstract: The present teaching relates to online task exchange. In one example, information related to a task automatically created based on an intent of a person is received. The task is posted to a plurality of parties that are capable of completing the task. One or more bids are received from at least some of the plurality of parties. At least one winning bid is selected from the one or more bids based on at least one criterion. Information indicative of a status as to completion of the task is received. Resource is allocated to the at least one winning bid based on the status.

Abstract: In one embodiment, a task to be performed by an individual may be identified based, at least in part, on content of one or more electronic communications transmitted between the individual and at least one other individual. Information pertaining to the task may be stored such that the task is added to a list or calendar. At least a portion of the information pertaining to the task may be provided for presentation via a client device.

Abstract: A first cluster of web objects is identified from a click-through data structure. The click-through data structure can organize web objects into clusters based on query results of web objects selected by a user. Also, a second cluster of web objects can be identified from a metadata data structure. The metadata data structure can organize web objects into clusters based on metadata associated with the web objects. An output set of web objects is selected, in real time, from the identifier clusters.

Abstract: A first cluster of web objects is identified from a click-through data structure. The click-through data structure can organize web objects into clusters based on query results of web objects selected by a user. Also, a second cluster of web objects can be identified from a metadata data structure. The metadata data structure can organize web objects into clusters based on metadata associated with the web objects. An output set of web objects is selected, in real time, from the identifier clusters.

Abstract: Duplicate video search results are detected and removed. Digital signatures are generated for each video content item of a video content corpus. Duplicates are determined for the top n previously received queries by determining the similarity of video content items that are within the same results set of each particular query of the top n previously received queries. Similarities are calculated between any two video documents of the result set of the particular query by measuring the difference between the digital signatures of two video documents. If a similarity between two videos is determined to be above a particular threshold, then the two videos are considered duplicates of each other and the search index is updated by retaining the most relevant of the video documents to the particular query. The less relevant video documents are flagged as duplicates with respect to the particular query.

Abstract: A first cluster of web objects is identified from a click-through data structure. The click-through data structure can organize web objects into clusters based on query results of web objects selected by a user. Also, a second cluster of web objects can be identified from a metadata data structure. The metadata data structure can organize web objects into clusters based on metadata associated with the web objects. An output set of web objects is selected, in real time, from the identifier clusters.

Abstract: Duplicate video search results are detected and removed. Digital signatures are generated for each video content item of a video content corpus. Duplicates are determined for the top n previously received queries by determining the similarity of video content items that are within the same results set of each particular query of the top n previously received queries. Similarities are calculated between any two video documents of the result set of the particular query by measuring the difference between the digital signatures of two video documents. If a similarity between two videos is determined to be above a particular threshold, then the two videos are considered duplicates of each other and the search index is updated by retaining the most relevant of the video documents to the particular query. The less relevant video documents are flagged as duplicates with respect to the particular query.