SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Ontology-based relevance analysis for automatic reference tracking
International Journal of Computer Applications in Technology
Finding related pages using Green measures: an illustration with Wikipedia
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Proceedings of the 18th ACM conference on Information and knowledge management
Learning to rank with (a lot of) word features
Information Retrieval
Comparative evaluation of ontology-based Automatic Reference Tracking (ART)
International Journal of Networking and Virtual Organisations
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Assessing semantic similarity between text documents is a crucial aspect in Information Retrieval systems. In this work, we propose to use hyperlink information to derive a similarity measure that can then be applied to compare any text documents, with or without hyperlinks. As linked documents are generally semantically closer than unlinked documents, we use a training corpus with hyperlinks to infer a function a,b → sim(a,b) that assigns a higher value to linked documents than to unlinked ones. Two sets of experiments on different corpora show that this function compares favorably with OKAPI matching on document retrieval tasks.