Advanced feedback methods in information retrieval
Journal of the American Society for Information Science
An evaluation of phrasal and clustered representations on a text categorization task
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Relevance feedback and inference networks
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Optimization of relevance feedback weights
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Document filtering with inference networks
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Learning routing queries in a query zone
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Improving automatic query expansion
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Separate-and-Conquer Rule Learning
Artificial Intelligence Review
Learning page-independent heuristics for extracting data from Web pages
WWW '99 Proceedings of the eighth international conference on World Wide Web
Interactive document retrieval with relational learning
Proceedings of the 2001 ACM symposium on Applied computing
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Interactive Web Page Filtering with Relational Learning
WI '01 Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development
The importance of proper weighting methods
HLT '93 Proceedings of the workshop on Human Language Technology
SVM-based interactive document retrieval with active learning
New Generation Computing
CyberIR --- A Technological Approach to Fight Cybercrime
PAISI, PACCF and SOCO '08 Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics
Learning to rank with document ranks and scores
Knowledge-Based Systems
An entropy-based query expansion approach for learning researchers' dynamic information needs
Knowledge-Based Systems
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In this paper we propose an approach for refining a document ranking by learning filtering rulesets through relevance feedback. This approach includes two important procedures. One is a filtering method, which can be incorporated into any kinds of information retrieval systems. The other is a learning algorithm to make a set of filtering rules, each of which specifies a condition to identify relevant documents using combinations of characteristic words. Our approach is useful not only to overcome the limitation of the vector space model, but also to utilize tags of semi-structured documents like Web pages. Through experiments we show our approach improves the performance of relevance feedback in two types of IR systems adopting the vector space model and a Web search engine, respectively.