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Probabilistic models of information retrieval based on measuring the divergence from randomness
Gianni Amati, Cornelis Joost Van Rijsbergen
We introduce and create a framework for deriving probabilistic models of Information Retrieval. The models are nonparametric models of IR obtained in the language model approach. We derive term-weighting models by measuring the divergence of...
A semantic network-based design methodology for XML documents
Ling Feng, Elizabeth Chang, Tharam Dillon
The eXtensible Markup Language (XML) is fast emerging as the dominant standard for describing and interchanging data among various systems and databases on the Internet. It offers the Document Type Definition (DTD) as a formalism for defining the...
Cumulated gain-based evaluation of IR techniques
Kalervo Järvelin, Jaana Kekäläinen
Modern large retrieval environments tend to overwhelm their users by their large output. Since all documents are not of equal relevance to their users, highly relevant documents should be identified and ranked first for presentation. In order to...