A Learning-Based Term-Weighting Approach for Information Retrieval

Book One

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 20

Semantic Web, Information Retrieval, and Extraction

One of the core components in information retrieval(IR) is the document-term-weighting scheme. In this paper,we will propose a novel learning-based term-weighting approach to improve the retrieval performance of vector space model in homogeneous collections. We first introduce a simple learning system to weighting the index terms of documents. Then, we deduce a formal computational approach according to some theories of matrix computation and statistical inference. Our experiments on 8 collections will show that our approach outperforms classic TF.IDF weighting, about 20%~45%.