Abstract:
Briefly, example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to facilitate and/or support one or more operations and/or techniques for in part, to facilitate and/or support one or more operations and/or techniques for ranking answers for on-line community questions.
Abstract:
Methods and devices for assessing the quality of user-generated content are described. In one embodiment, a method is disclosed for measuring the quality of a user-generated answer to a question by combining various factors, including question-answer surface word vector similarity, question-answer explicit semantic analysis vector similarity, answer-answer explicit sematic analysis vector similarity, query performance predictor, sentiment analysis, textual analysis of the answer, and reputation of the answerer. The method uses a learning procedure to determine the best algorithm for measuring the overall quality of the answer based on these factors.
Abstract:
Methods and devices for assessing the quality of user-generated content are described. In one embodiment, a method is disclosed for measuring the quality of a user-generated answer to a question by combining various factors, including question-answer surface word vector similarity, question-answer explicit semantic analysis vector similarity, answer-answer explicit sematic analysis vector similarity, query performance predictor, sentiment analysis, textual analysis of the answer, and reputation of the answerer. The method uses a learning procedure to determine the best algorithm for measuring the overall quality of the answer based on these factors.
Abstract:
Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods automatically generate and provide an interactive rich set of personalized query suggestions within a unified framework. The disclosed systems and methods are able to integrate attributes associated with message data and metadata by transforming such attributes into facets that are combined with term suggestions and presented to the user in a unified manner. The instant disclosure provides an interactive search suggestion mechanism that narrows the search as the user interacts with the dynamically generated and provided suggestions.
Abstract:
Methods, systems and programming for predicting search results quality. In one example, a search query is received from a user. A plurality of search results are obtained from a content source based on the search query. The plurality of search results are ranked based on their relevance scores with respect to the search query. A distribution of the relevance scores of the plurality of search results is normalized in each position of the ranking. A metric of the content source is computed based on the normalized distribution of the relevance scores. The metric indicates a relevance between the plurality of search results and the search query.
Abstract:
Relevant messages, or “hero results”, which are not ranked at the uppermost part of a time-based listing of search results are identified and such hero results can be displayed apart from the time-based listing of search results. A user can be provided with messages in a time-based presentation as well as messages in a relevance-based presentation. The user can be presented with the most relevant messages from a set of message generated from a search query, even where the most relevant messages are not the most recent ones.
Abstract:
Methods, systems and programming for predicting search results quality. In one example, a search query is received from a user. A plurality of search results are obtained from a content source based on the search query. The plurality of search results are ranked based on their relevance scores with respect to the search query. A distribution of the relevance scores of the plurality of search results is normalized in each position of the ranking. A metric of the content source is computed based on the normalized distribution of the relevance scores. The metric indicates a relevance between the plurality of search results and the search query.
Abstract:
Methods and apparatus for performing top-k query processing include pruning a list of documents to identify a subset of the list of documents, where pruning includes, for other query terms in the set of query terms, skipping a document in the list of documents based, at least in part, on the contribution of the query term to the score of the corresponding document and the term upper bound for each other query term, in the set of query terms, that matches the document.
Abstract:
A search query for searching electronic messages, such as email, may be used to search for different types of items, such as and without limitation electronic messages, contacts, photos, documents, such as and without limitation papers, presentations, etc., business entities, personal information extracted from messages, such as and without limitation purchase orders, shipments, reservations, travel itineraries, etc. Several sources of data, which may be indexed for searching, such as and without limitation a personal mail search index, contacts, or business entity, index, attachments index, extracted data index, etc. may be searched using the search query. A number of top search result items, which may include different types of items, may be presented apart from other search result items.