Abstract: Techniques for unsupervised management of a question and answer (QA) forum include labeling of answers for quality purposes, and identification of experts. In a QA thread, a ranking of answers may include an initial labeling of the longest answer in each thread as the best answer. Such a labeling provides an initial point of reference. Then, in an iterative manner answerers are ranked using the labeling. The ranking of answerers allows selection of experts and poor or inexpert answerers. A label update is performed using the experts (and perhaps inexpert answerers) as input. The label update may be used to train a model, which may describe quality of answers in one or more QA threads and an indication of expert and inexpert answerers. The iterative process may be ended upon convergence or upon a maximum number of iterations.

Abstract: Techniques for unsupervised management of a question and answer (QA) forum include labeling of answers for quality purposes, and identification of experts. In a QA thread, a ranking of answers may include an initial labeling of the longest answer in each thread as the best answer. Such a labeling provides an initial point of reference. Then, in an iterative manner answerers are ranked using the labeling. The ranking of answerers allows selection of experts and poor or inexpert answerers. A label update is performed using the experts (and perhaps inexpert answerers) as input. The label update may be used to train a model, which may describe quality of answers in one or more QA threads and an indication of expert and inexpert answerers. The iterative process may be ended upon convergence or upon a maximum number of iterations.

Abstract: Described herein are techniques for extracting data records containing user-generated content from documents. The documents may be processed into document trees in which sub-trees represent the data records of the document. Domain constraints may be used to locate structured portions of the document tree. For example, anchor trees may be located as being sets of sibling sub-trees with similar tag paths that contain the domain constraints. The anchor trees may then be used to determine a record boundary (e.g., the start offset and length) of the data records. Finally, the data records may be extracted based on the anchor trees and the record boundaries.

Abstract: Embodiments for a Mining Data Records based on Anchor Trees (MiBAT) process are disclosed. In accordance with at least one embodiment, the MiBAT process extracts data records containing user-generated content from web documents. The web document is processed into a Document Object Model (DOM) tree in which sub-trees of the DOM tree represent the data records of the web document. Domain constraints are used to locate structured portions of the DOM tree. Anchor trees are then located as being sets of sibling sub-trees which contain the domain constraints. The anchor trees are then used to determine a record boundary (i.e. the start offset and length) of the data records. Finally, the data records are extracted based on the anchor trees and the record boundaries.

Abstract: A question search system provides a collection of questions having words for use in evaluating the utility of the questions based on a language model. The question search system calculates n-gram probabilities for words within the questions of the collection. The n-gram probability of a word for a sequence of n?1 words indicates the probability of that word being next after that sequence in the collection of questions. The n-gram probabilities for the words of the collection represent the language model of the collection. The question search system calculates a language model utility score for each question within a collection that indicates the likelihood that a question is repeatedly asked by users. The question search system derives the language model utility score for a question from the n-gram probabilities of the words within that question.

Abstract: One or more techniques and systems are disclosed for generating comparative patterns for use in identifying comparators. A set of comparator pairs is extracted from a first comparative pattern in a pattern database that comprises one or more comparative patterns. Questions are retrieved from a question collection using respective comparator pairs to generate comparative questions. Potential comparative patterns are generated from a combination of the comparator pairs and comparative questions, and the potential comparative patterns are evaluated by determining their reliability, in order to generate second comparative patterns for the pattern database.

Abstract: A method and system for determining the relevance of questions to a queried question based on topics and focuses of the questions is provided. A question search system provides a collection of questions with topics and focuses. Upon receiving a queried question, the question search system identifies a queried topic and queried focus of the queried question. The question search system generates a score indicating the relevance of a question of the collection to the queried question based on a language model of the topic of the question and a language model of the focus of the question.

Abstract: A method and system for presenting questions that are relevant to a queried question based on clusters of topics and clusters of focuses of the questions is provided. A question search system provides a collection of questions. Each question of the collection has an associated topic and focus. Upon receiving a queried question, the question search system identifies questions of the collection that may be relevant to the queried question and generates a score or ranking indicating relevance of the identified questions. The question search system clusters the identified questions into topic clusters of questions with similar topics. The question search system may also cluster the questions within each topic cluster into focus clusters of questions with similar focuses.

Abstract: In a question answering system, the system identifies a type of question input by a user. The system then generates answer summaries that summarize answers to the input question in a format that is determined based on the type of question asked by the user. The answer summaries are output, in the corresponding format, in answer to the input question.

Abstract: Exemplary methods, computer-readable media, and systems are presented for learning to recommend questions and other user-generated submissions to community sites based on user ratings. The size of available training data is enlarged by taking into consideration questions without user ratings, which in turn benefits the learned model. Question or other user-generated submissions are obtained by crawling Internet-accessible Web sites including community sites. Questions and other submissions, even when not tagged, voted or indicated as “popular” or “interesting” by users are quantitatively indentified as “interesting.

Abstract: Exemplary methods, computer-readable media, and systems are presented for leveraging question-answering knowledge from community sites by complementing product search services with a search of questions, answers, reviews and other Internet accessible content including user-generated content. Product or service information is obtained by crawling Internet-accessible Web sites including community sites. An integrated index of such information is generated. A user is able to browse questions by product or service feature, by topic, by identified comparative questions, and by question ranking (for example, interestingness or popularity).

Abstract: A probability distribution for a reference summary of a document is determined. The probability distribution for the reference summary is then used to generate a score for a machine-generated summary of the document.

Abstract: In this paper, we propose a new approach to extracting question-context-answer triples from online discussion forums. More specifically, we propose a general framework based on Conditional Random Fields (CRFs) for context and answer detection, and also extend the basic framework to utilize contexts for answer detection and to better accommodate the features of forums.

Abstract: The present invention provides a new approach to extracting question-answer pairs from online forums. The system develops a classification-based technique to discover questions in forums using sequential patterns automatically extracted from both questions and non-question sentences in forums as features. Once the questions are discovered, the system discovers the answers. The invention includes a graph-based method is that it is complementary with supervised methods for knowledge extraction, and techniques for question answering.

Abstract: A question search system provides a collection of questions having words for use in evaluating the utility of the questions based on a language model. The question search system calculates n-gram probabilities for words within the questions of the collection. The n-gram probability of a word for a sequence of n?1 words indicates the probability of that word being next after that sequence in the collection of questions. The n-gram probabilities for the words of the collection represent the language model of the collection. The question search system calculates a language model utility score for each question within a collection that indicates the likelihood that a question is repeatedly asked by users. The question search system derives the language model utility score for a question from the n-gram probabilities of the words within that question.

Abstract: A method and system for determining the relevance of questions to a queried question based on topics and focuses of the questions is provided. A question search system provides a collection of questions with topics and focuses. Upon receiving a queried question, the question search system identifies a queried topic and queried focus of the queried question. The question search system generates a score indicating the relevance of a question of the collection to the queried question based on a language model of the topic of the question and a language model of the focus of the question.

Abstract: A method and system for presenting questions that are relevant to a queried question based on clusters of topics and clusters of focuses of the questions is provided. A question search system provides a collection of questions. Each question of the collection has an associated topic and focus. Upon receiving a queried question, the question search system identifies questions of the collection that may be relevant to the queried question and generates a score or ranking indicating relevance of the identified questions. The question search system clusters the identified questions into topic clusters of questions with similar topics. The question search system may also cluster the questions within each topic cluster into focus clusters of questions with similar focuses.

Abstract: In a question answering system, the system identifies a type of question input by a user. The system then generates answer summaries that summarize answers to the input question in a format that is determined based on the type of question asked by the user. The answer summaries are output, in the corresponding format, in answer to the input question.

Abstract: The present system graphs topic terms in stored cQA questions and also converts a submitted question into a graph of topic terms. Topic terms that correspond to a question topic are delineated from topic terms that correspond to question focus. New questions are recommended to the user based on a comparison between the topics of the new questions and the topic of the submitted question as well as the focus of the new questions and the focus of the submitted question.

Abstract: A method for handling product reviews can detect a first quality product review from a second quality product review. The first and second quality product reviews can be associated with a product. The first quality product review can be filtered. An opinion segment in the second quality product review can be identified and the polarity can be determined of the opinion segment. An opinion set can be generated with the opinion segment for a product feature. A score (or weighty can be aggregated of segments in the opinion set for the product feature.