A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
HLT '02 Proceedings of the second international conference on Human Language Technology Research
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This paper presents the results of the State University of New York at Buffalo (UB) in the Mono-lingual and Multi-lingual tasks at CLEF 2004. For these tasks we used an approach based on statistical language modeling. Our Adhoc retrieval work used the TAPIR toolkit developed in house by M Srikanth. Our approach focused on the validation and adaptation of the language model system to work in a multilingual environment and in exploring ways to merge results from multiple collections into a single list of results. We explored the use of a measure of query ambiguity, also known as clarity score, for merging results of the individual collections into a single list of retrieved documents. Our results indicate that the use of clarity scores normalized across queries gives statistically significant improvements over using a fixed merging order.