Perspectives on electronic publishing: standards, solutions, and more
Perspectives on electronic publishing: standards, solutions, and more
Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
IR evaluation methods for retrieving highly relevant documents
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Hubs, authorities, and communities
ACM Computing Surveys (CSUR)
Machine Learning
Machine Learning
Computational Statistics & Data Analysis - Nonlinear methods and data mining
The Alternating Decision Tree Learning Algorithm
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
A framework to predict the quality of answers with non-textual features
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Expertise networks in online communities: structure and algorithms
Proceedings of the 16th international conference on World Wide Web
Finding high-quality content in social media
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Quality-aware collaborative question answering: methods and evaluation
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Broad-coverage sense disambiguation and information extraction with a supersense sequence tagger
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Evaluating and predicting answer quality in community QA
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Using graded-relevance metrics for evaluating community QA answer selection
Proceedings of the fourth ACM international conference on Web search and data mining
Automatic Assessment of Document Quality in Web Collaborative Digital Libraries
Journal of Data and Information Quality (JDIQ)
Analyzing and predicting question quality in community question answering services
Proceedings of the 21st international conference companion on World Wide Web
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Automatic identification of best answers in online enquiry communities
ESWC'12 Proceedings of the 9th international conference on The Semantic Web: research and applications
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Collaborative web sites, such as collaborative encyclopedias, blogs, and forums, are characterized by a loose edit control, which allows anyone to freely edit their content. As a consequence, the quality of this content raises much concern. To deal with this, many sites adopt manual quality control mechanisms. However, given their size and change rate, manual assessment strategies do not scale and content that is new or unpopular is seldom reviewed. This has a negative impact on the many services provided, such as ranking and recommendation. To tackle with this problem, we propose a learning to rank (L2R) approach for ranking answers in Q&A forums. In particular, we adopt an approach based on Random Forests and represent query and answer pairs using eight different groups of features. Some of these features are used in the Q&A domain for the first time. Our L2R method was trained to learn the answer rating, based on the feedback users give to answers in Q&A forums. Using the proposed method, we were able (i) to outperform a state of the art baseline with gains of up to 21% in NDCG, a metric used to evaluate rankings; we also conducted a comprehensive study of the features, showing that (ii) review and user features are the most important in the Q&A domain although text features are useful for assessing quality of new answers; and (iii) the best set of new features we proposed was able to yield the best quality rankings.