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
Searching distributed collections with inference networks
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Learning collection fusion strategies
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
STARTS: Stanford proposal for Internet meta-searching
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Experiences with selecting search engines using metasearch
ACM Transactions on Information Systems (TOIS)
A probabilistic model for distributed information retrieval
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
On the fusion of documents from multiple collection information retrieval systems
Journal of the American Society for Information Science
Merging techniques for performing data fusion on the web
Proceedings of the tenth international conference on Information and knowledge management
Independence of contributing retrieval strategies in data fusion for effective information retrieval
IRSG'98 Proceedings of the 20th Annual BCS-IRSG conference on Information Retrieval Research
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In information retrieval, the data fusion problem is as follows: given two or more independent retrieved sets of ranked documents in response to the same query, how to merge the sets in order to present the user with the most effective ranking? We propose a formal model for data fusion that is based on the knowledge that can be derived from the retrieved documents. The modelis based on evidential reasoning, a theory that formally expresses knowledge and the combination of knowledge. Knowledge characterising a ranked list of retrieved documents is symbolised. The combination of knowledge associated to the several retrieval results yields the characterisation of the merged result.