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 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:
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 sentiment classifier is described. In one implementation, a system applies both full text and complex feature analyses to sentences of a product review. Each analysis is weighted prior to linear combination into a final sentiment prediction. A full text model and a complex features model can be trained separately offline to support online full text analysis and complex features analysis. Complex features include opinion indicators, negation patterns, sentiment-specific sections of the product review, user ratings, sequence of text chunks, and sentence types and lengths. A Conditional Random Field (CRF) framework provides enhanced sentiment classification for each segment of a complex sentence to enhance sentiment prediction.
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 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:
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 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:
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.