Information Processing and Management: an International Journal
Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Automatic combination of multiple ranked retrieval systems
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
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
Pivoted document length normalization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Analyses of multiple evidence combination
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Results and challenges in Web search evaluation
WWW '99 Proceedings of the eighth international conference on World Wide Web
Web search behavior of Internet experts and newbies
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
A case study in web search using TREC algorithms
Proceedings of the 10th international conference on World Wide Web
Effective site finding using link anchor information
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
The Importance of Prior Probabilities for Entry Page Search
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
WIDIT: integrated approach to HARD topic search
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
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To facilitate both the understanding and the discovery of information, we need to utilize multiple sources of evidence, integrate a variety of methodologies, and combine human capabilities with those of the machine. The Web Information Discovery Integrated Tool (WIDIT) Laboratory at the School of Library and Information Science, Indiana University-Bloomington, houses several projects that employ this idea of multi-level fusion in the areas of information retrieval and knowledge discovery. This paper describes a Web search optimization study by the TREC research group of WIDIT, who explores a fusion-based approach to enhancing retrieval performance on the Web. In the study, we employed both static and dynamic tuning methods to optimize the fusion formula that combines multiple sources of evidence. By static tuning, we refer to the typical stepwise tuning of system parameters based on training data. “Dynamic tuning”, the key idea of which is to combine the human intelligence, especially pattern recognition ability, with the computational power of the machine, involves an interactive system tuning process that facilitates fine-tuning of the system parameters based on the cognitive analysis of immediate system feedback. The rest of the paper is organized as follows. The next section discusses related work in Web information retrieval (IR). Section 3 details the WIDIT approach to Web IR, followed by the description of our experiment using the TREC .gov data in section 4 and the discussion of results in section 5.