Abstract: Multiple machine learning models can be jointly trained in parallel. An example process for jointly training multiple machine learning models includes providing a set of machine learning models that are to learn a respective task, the set of machine learning models including a first machine learning model and a second machine learning model. The process can initiate training of the first machine learning model to learn a task using training data. During the training of the first machine learning model, information can be passed between the first machine learning model and the second machine learning model. Such passing of information (or “transfer of knowledge”) between the machine learning models can be accomplished via the formulation, and optimization, of an objective function that comprises model parameters that are based on the multiple machine learning models in the set.

Abstract: Functionality is described for identifying a discussion topic based on user interest information. The user interest information may originate from one or more sources, such as the user's search-related behavior. The functionality then provides an opportunity for the user to engage in a communication exchange associated with the identified discussion topic.

Abstract: A system for guiding a search for information is presented. The system comprises a user interface that accepts a phrase and receives at least one suggestion based at least in part on the phrase. The system also includes a phrase suggestion engine that matches the phrase with the at least one suggestion. Methods of using the system are also provided.

Abstract: Functionality is described for identifying a discussion topic based on user interest information. The user interest information may originate from one or more sources, such as the user's search-related behavior. The functionality then provides an opportunity for the user to engage in a communication exchange associated with the identified discussion topic.

Abstract: A system for guiding a search for information is presented. The system comprises a user interface that accepts a phrase and receives at least one suggestion based at least in part on the phrase. The system also includes a phrase suggestion engine that matches the phrase with the at least one suggestion. Methods of using the system are also provided.

Abstract: A system for guiding a search for information is presented. The system comprises a user interface that accepts a phrase and receives at least one suggestion based at least in part on the phrase. The system also includes a phrase suggestion engine that matches the phrase with the at least one suggestion. Methods of using the system are also provided.

Abstract: Conventionally, there are communities of individuals who perform Internet searches and communities of individuals who utilized Internet communications. While there is commonly a large amount of overlap between the two communities, there is little interaction between the two communities. Internet searches can be used to recommend interesting people to a user. Furthermore, Internet communications can be used to recommend content that is likely to be of interest to the user. In addition, previously engaged communications or searches can be used to disambiguate terms in a subsequent search.

Abstract: Methods and computer-readable media are provided for receiving keyword expansions from expansion providers and selecting a set of keyword expansions that are used for advertisement selection. Keyword expansions that correspond to a particular search query or text from a browsed web page are received from an expansion provider. Feature data is extracted from each keyword expansion, and may include properties of the keyword expansion or the expansion provider. A score is assigned to each keyword expansion, and based on the score, a set of keyword expansions is selected from the keyword expansions received from the expansion provider. The set of keyword expansions is used to select relevant advertisements for presentation to the user.

Abstract: A system for associating information comprises an association module that uses anchoring information to associate a first piece of information with a second piece of information, wherein the second piece of information is not part of the first piece of information. The system further includes a rendering module that presents the second piece of information for use. Methods for using such a system are also described.

Abstract: Functionality is described for identifying a discussion topic based on user interest information. The user interest information may originate from one or more sources, such as the user's search-related behavior. The functionality then provides an opportunity for the user to engage in a communication exchange associated with the identified discussion topic.

Abstract: The subject invention relates to a system and/or methodology that facilitate converting structured data (e.g., tabular information) into natural language, thus making it available to question answering systems and search engines. More specifically, the system and method employ the vast quantities of natural language on the particular storage system, database, network, or server that a user wishes to search. For example, the system can utilize natural-language based information located on the Web to assist in the task of converting structured data into natural language. In particular, the system can find at least one sentence or sentence fragment on the Web that refers to at least one tuple (e.g., row) in a given table. Following, those sentences can be generalized across all or substantially all tuples in the table. The resulting body of text can be used by the question answering system to answer user queries.

Abstract: A unique ranking system and method that facilitates improving the ranking and ordering of objects to further enhance the quality, accuracy, and delivery of search results in response to a search query. The system and method involve monitoring and tracking an object in terms of the number of times it's been accessed and optionally by whom, when, for how long, and an access rate. The user's interaction with the object can be tracked as well. By tracking the objects, a popularity measure can be determined. Popularity based rankings can be computed based on the popularity measure or some function thereof. The popularity measure can be affected by the access time, who accessed it, access duration or the user's interaction with the object upon access. The popularity based rankings can be utilized by a search component to improve the quality and retrieval of search results.

Abstract: A system for associating information comprises an association module that uses anchoring information to associate a first piece of information with a second piece of information, wherein the second piece of information is not part of the first piece of information. The system further includes a rendering module that presents the second piece of information for use. Methods for using such a system are also described.

Abstract: Aspects of the subject matter described herein relate to predicting a best search engine to use for a given query. In aspects, a predictor may use various approaches to determine a best search engine for a given query. For example, the predictor may use features derived from the query itself, how well the query matches a result set returned by a search engine in response to the query, and/or information that compares the result sets returned by multiple search engines that are provided the query. In addition, other data such as user preferences, user interaction data, metadata attributes, and/or other data may be used in predicting a best search engine for a given query. In conjunction with making a prediction, the predictor may use a classifier that has been trained at a training facility.

Abstract: A system for guiding a search for information is presented. The system comprises a user interface that accepts a phrase and receives at least one suggestion based at least in part on the phrase. The system also includes a phrase suggestion engine that matches the phrase with the at least one suggestion. Methods of using the system are also provided.

Abstract: Systems and methods that provide search and/or query-relevant information and/or links thereto to a user as and/or with a search and/or query result. This information can be determined from summary information that can be included within a tag, header, body, meta-data, etc. of the data. A user can employ a local and/or web search utility along with a search word, phrase, sentence, etc. to search over a data repository to locate and retrieve data that satisfies the search criteria. The summary information of this data is obtained and matched against the results and/or search criteria to determine whether the data is relevant to the search and/or query. The summary information is utilized to determine a snippet that summarizes the data, based on the search and/or query, search criteria, etc. to provide the user with search and/or query-relevant results and/or one or more links thereto.

Abstract: Conventionally, there are communities of individuals who perform Internet searches and communities of individuals who utilized Internet communications. While there is commonly a large amount of overlap between the two communities, there is little interaction between the two communities. Internet searches can be used to recommend interesting people to a user. Furthermore, Internet communications can be used to recommend content that is likely to be of interest to the user. In addition, previously engaged communications or searches can be used to disambiguate terms in a subsequent search.

Abstract: A system for guiding a search for information is presented. The system comprises a user interface that accepts a phrase and receives at least one suggestion based at least in part on the phrase. The system also includes a phrase suggestion engine that matches the phrase with the at least one suggestion. Methods of using the system are also provided.

Abstract: Systems, methods, and computer-readable media for estimating expected advertisement performance of advertisements are provided. An advertisement performance prediction model is developed using features extracted from a sample set. Once developed, advertisements that are not a part of the sample set are identified and features are extracted there from. The features are then input into the advertisement performance prediction model and expected performance of the corresponding advertisement is estimated. In embodiments, the estimated expected advertisement performance may be used to appropriately rank the advertisement relative to a plurality of other advertisements such that the advertisement will be displayed according to the advertisement ranking.

Abstract: The relevancy of search results are improved by exploiting changes in data related to information access. Parameter varying aspects of parameter varying data associated with document access are leveraged to provide enhanced ranking of document. As an aspect of the parameter varies, a rank can be accomplished, producing multiple ranks for a given set of parameter varying data. Parameters such as time, user preferences, popularity, and/or user demographics and the like can be utilized as parameter varying data. Thus, in general, single or multiple varying aspects of the parameters can be employed to produce a set of ranks comprising one or more rankings of document. This technique can be employed with static rankers, dynamic rankers, and/or ranker training data and the like to produce higher relevancy search results, increasing user satisfaction.