Term weighting for information retrieval based on term’s discrimination power

One of the most important research topics in Information Retrieval is term weighting for document ranking and retrieval, such as TFIDF, BM25, etc. We propose a term weighting method that utilizes past retrieval results consisting of the queries that contain a particular term, retrieval documents, and their relevance judgments. A term’s Discrimination Power(DP) is based on the difference degree of the term’s average weights obtained from between relevant and non-relevant retrieved document sets. The difference based DP performs better compared to ratio based DP introduced in the previous research. Our experimental result shows that a term weighting scheme based on the discrimination power method outperforms a TF*IDF based scheme.