Recent trends in hierarchic document clustering: a critical review
Information Processing and Management: an International Journal
Information retrieval
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using lexical-semantic relations
SIGIR '94 Proceedings of the 17th 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
Reexamining the cluster hypothesis: scatter/gather on retrieval results
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Exploiting clustering and phrases for context-based information retrieval
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Customizable multi-engine search tool with clustering
Selected papers from the sixth international conference on World Wide Web
ECHO: An Information Gathering Agent
ECHO: An Information Gathering Agent
ADC '01 Proceedings of the 12th Australasian database conference
Clustering and Classification in Structured Data Domains Using Fuzzy Lattice Neurocomputing (FLN)
IEEE Transactions on Knowledge and Data Engineering
Association Rule Extraction for Text Mining
FQAS '02 Proceedings of the 5th International Conference on Flexible Query Answering Systems
An Agent-Based Personalized Search on a Multi-Search Engine Based on Internet Search Service
IDEAL '00 Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents
Dialogue for Web Search Utilizing Automatically Acquired Domain Knowledge
TSD '01 Proceedings of the 4th International Conference on Text, Speech and Dialogue
Using web structure and summarisation techniques for web content mining
Information Processing and Management: an International Journal
Content-based audio retrieval with relevance feedback
Pattern Recognition Letters
Incorporating real-valued multiple instance learning into relevance feedback for image retrieval
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Effective and efficient classification on a search-engine model
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Evaluating WordBars in exploratory Web search scenarios
Information Processing and Management: an International Journal
VisiQ: Supporting visual and interactive query refinement
Web Intelligence and Agent Systems
Effective and efficient classification on a search-engine model
Knowledge and Information Systems
Filtering and Sophisticated Data Processing for Web Information Gathering
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Semantic retrieval of events from indoor surveillance video databases
Pattern Recognition Letters
Concept mining for indexing medical literature
Engineering Applications of Artificial Intelligence
Using Web structure and summarisation techniques for Web content mining
Information Processing and Management: an International Journal
Adaptive classification of web documents to users interests
PCI'01 Proceedings of the 8th Panhellenic conference on Informatics
Concept mining for indexing medical literature
MLDM'05 Proceedings of the 4th international conference on Machine Learning and Data Mining in Pattern Recognition
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The World Wide Web is a world of great richness, but finding information on the Web is also a great challenge. Keyword-based querying has been an immediate and efficient way to specify and retrieve related information that the user inquires. However, conventional document ranking based on an automatic assessment ofdocument relevance to the query may not be the best approach when little information is given, as in most cases. In order to clarify the ambiguity of the short queries given by users, we propose the idea of concept-based relevance feedback for Web information retrieval. The idea is to have users give two to three times more feedback in the same amount of time that would be required to give feedback for conventional feedback mechanisms. Under this design principle, we apply clustering techniques to the initial search results to provide concept-based browsing. We show the performances of various feedback interface designs and compare their pros and cons. We shall measure precision and relative recall to show how clustering improves performance over conventional similarity ranking and, most importantly, we shall show how the assistance of concept-based presentation reduces browsing labor.