Abstract: Methods, systems, and apparatus for accessing a set of feedback items, identifying a candidate feedback item from the set of feedback items using a lexical pattern, generating a gist phrase that summarizes the candidate feedback item, and causing display of a user interface on a client device, the user interface including the gist phrase.

Abstract: Methods, systems, and apparatus for mining feedback are described. A set of one or more lexical patterns associated with one or more of a suggestion and a defect report are determined and the set of one or more lexical patterns are matched against a plurality of feedback items to generate a distance learning training set. A distance learning technique is applied to the distance learning training set to generate a distance learning model and the distance learning model is used to identify one or more candidate feedback items of the plurality of feedback items, each of which is one or more of a candidate suggestion and a candidate defect report.

Abstract: Each user is represented by a mixture of topics, e.g., one or more topics, and a probability of interest in each topic in the mixture, and given the target user, one or more other users can be recommended, each user that is recommended to the target user is determined to have a topical interest similarity with the target user, e.g., the target user's interest in one or more topics of the mixtures of topics is determined to be similar to a recommended interest in the one or more topics of the mixture of topics. The target user and the one or more recommended users can be said to have similar topical interests. The target user can use the user recommendation to establish an interactive dialogue, for example, with one or more users identified in the user recommendation.

Abstract: Example embodiments described herein disclose systems and methods for near-identical multi-faceted entity identification within search results from an online marketplace. The online marketplace may be or include a group of one or more server machines configured to provide one or more online marketplace services, including the near-identical multi-faceted entity identification system. A user device may accordingly request and receive, from the online marketplace, a set of item listings based on submitted search criteria. The online marketplace may then access the set of item listings and identify one or more similar item listings among the set of item listings in order to demote a ranking of the similar item listings within the set.

Abstract: Methods, systems, and apparatus for mining feedback are described. A set of one or more lexical patterns associated with one or more of a suggestion and a defect report are determined and the set of one or more lexical patterns are matched against a plurality of feedback items to generate a distance learning training set. A distance learning technique is applied to the distance learning training set to generate a distance learning model and the distance learning model is used to identify one or more candidate feedback items of the plurality of feedback items, each of which is one or more of a candidate suggestion and a candidate defect report.

Abstract: Methods, systems, and apparatus for mining feedback are described. A set of one or more lexical patterns associated with one or more of a suggestion and a defect report are determined and the set of one or more lexical patterns are matched against a plurality of feedback items to generate a distance learning training set. A distance learning technique is applied to the distance learning training set to generate a distance learning model and the distance learning model is used to identify one or more candidate feedback items of the plurality of feedback items, each of which is one or more of a candidate suggestion and a candidate defect report.

Abstract: Disclosed are methods and apparatus for classifying users. In accordance with one embodiment, a plurality of messages posted by a user via a microblogging service may be obtained. A set of feature values associated with the user may be obtained, each of the set of feature values corresponding to a different one of a set of one or more features. One or more of the set of feature values may be obtained based, at least in part, on content of the plurality of messages posted by the user, messaging behavior of the user via the microblogging service, and/or social connections of the user established via the microblogging service. The user may be classified based upon the set of feature values associated with the user.

Abstract: Each user is represented by a mixture of topics, e.g., one or more topics, and a probability of interest in each topic in the mixture, and given the target user, one or more other users can be recommended, each user that is recommended to the target user is determined to have a topical interest similarity with the target user, e.g., the target user's interest in one or more topics of the mixtures of topics is determined to be similar to a recommended interest in the one or more topics of the mixture of topics. The target user and the one or more recommended users can be said to have similar topical interests. The target user can use the user recommendation to establish an interactive dialogue, for example, with one or more users identified in the user recommendation.

Abstract: Example embodiments described herein disclose systems and methods for near-identical multi-faceted entity identification within search results from an online marketplace. The online marketplace may be or include a group of one or more server machines configured to provide one or more online marketplace services, including the near-identical multi-faceted entity identification system. A user device may accordingly request and receive, from the online marketplace, a set of item listings based on submitted search criteria. The online marketplace may then access the set of item listings and identify one or more similar item listings among the set of item listings in order to demote a ranking of the similar item listings within the set.

Abstract: Each user is represented by a mixture of topics, e.g., one or more topics, and a probability of interest in each topic in the mixture, and given the target user, one or more other users can be recommended, each user that is recommended to the target user is determined to have a topical interest similarity with the target user, e.g., the target user's interest in one or more topics of the mixtures of topics is determined to be similar to a recommended interest in the one or more topics of the mixture of topics. The target user and the one or more recommended users can be said to have similar topical interests. The target user can use the user recommendation to establish an interactive dialogue, for example, with one or more users identified in the user recommendation.

Abstract: Methods, systems, and apparatus for mining feedback are described. A set of one or more lexical patterns associated with one or more of a suggestion and a defect report are determined and the set of one or more lexical patterns are matched against a plurality of feedback items to generate a distance learning training set. A distance learning technique is applied to the distance learning training set to generate a distance learning model and the distance learning model is used to identify one or more candidate feedback items of the plurality of feedback items, each of which is one or more of a candidate suggestion and a candidate defect report.

Abstract: A method, device, and computer-readable storage medium storing instructions are provided for detecting controversial events that are reflected in user-generated content items. In a single-step approach, user-generated content items are received and analyzed by a controversial event detection module, which determines the likelihood that sets of content items reflect controversial events. In one example, public posts by users of a social networking service are grouped into snapshots of posts that are associated with an entity and were generated during a window of time. An event detection module may determine the likelihood that snapshots reflect events. In a two-step approach, event snapshots are provided to a controversy detection module, which determines the likelihood that event snapshots are controversial. In a blended approach, snapshots are provided to a controversy detection module, which determines the likelihood that snapshots are controversial events based in part on the event score.

Abstract: In an example embodiment, a first social media profile is retrieved. Express interests in the first social media profile are extracted, and social media categories corresponding to the express interests are identified. Demographic information is also extracted from the first social media profile. Then, the identified social media categories and demographic information are correlated with ecommerce categories of purchases. Using results from the correlating, a machine learning process is configured, the machine learning process accepting a second social media profile as input and returning a prediction of an ecommerce category as output.

Abstract: The disclosed embodiments of computer systems and techniques utilize an ensemble semantics framework to combine knowledge acquisition systems that yield significantly higher quality resources than each system in isolation. Gains in entity extraction are achieved by combining state-of-the-art distributional and pattern-based systems with a large set of features from, for example, a webcrawl, query logs, and wisdom of the crowd sources. This results in improved query interpretation and greater relevancy in providing search results and advertising, for example.

Abstract: Each user is represented by a mixture of topics, e.g., one or more topics, and a probability of interest in each topic in the mixture, and given the target user, one or more other users can be recommended, each user that is recommended to the target user is determined to have a topical interest similarity with the target user, e.g., the target user's interest in one or more topics of the mixtures of topics is determined to be similar to a recommended interest in the one or more topics of the mixture of topics. The target user and the one or more recommended users can be said to have similar topical interests. The target user can use the user recommendation to establish an interactive dialogue, for example, with one or more users identified in the user recommendation.

Abstract: Disclosed are methods and apparatus for classifying users. In accordance with one embodiment, a plurality of messages posted by a user via a microblogging service may be obtained. A set of feature values associated with the user may be obtained, each of the set of feature values corresponding to a different one of a set of one or more features. One or more of the set of feature values may be obtained based, at least in part, on content of the plurality of messages posted by the user, messaging behavior of the user via the microblogging service, and/or social connections of the user established via the microblogging service. The user may be classified based upon the set of feature values associated with the user.

Abstract: A method, device, and computer-readable storage medium storing instructions are provided for detecting controversial events that are reflected in user-generated content items. In a single-step approach, user-generated content items are received and analyzed by a controversial event detection module, which determines the likelihood that sets of content items reflect controversial events. In one example, public posts by users of a social networking service are grouped into snapshots of posts that are associated with an entity and were generated during a window of time. An event detection module may determine the likelihood that snapshots reflect events. In a two-step approach, event snapshots are provided to a controversy detection module, which determines the likelihood that event snapshots are controversial. In a blended approach, snapshots are provided to a controversy detection module, which determines the likelihood that snapshots are controversial events based in part on the event score.

Abstract: The disclosed embodiments of computer systems and techniques utilize an ensemble semantics framework to combine knowledge acquisition systems that yield significantly higher quality resources than each system in isolation. Gains in entity extraction are achieved by combining state-of-the-art distributional and pattern-based systems with a large set of features from, for example, a webcrawl, query logs, and wisdom of the crowd sources. This results in improved query interpretation and greater relevancy in providing search results and advertising, for example.

Abstract: The disclosed embodiments of computer systems and techniques utilize an ensemble semantics framework to combine knowledge acquisition systems that yield significantly higher quality resources than each system in isolation. Gains in entity extraction are achieved by combining state-of-the-art distributional and pattern-based systems with a large set of features from, for example, a webcrawl, query logs, and wisdom of the crowd sources. This results in improved query interpretation and greater relevancy in providing search results and advertising, for example.