Analysis of Document Diversity through Sentence-Level Opinion and Relation Extraction

Abstract

Diversity in document retrieval has been mainly approached as a classical statistical problem, where the typical optimization function aims at diversifying the retrieval items represented by means of language models. Although this is an essential step for the development of effective approaches to capture diversity, it is clearly not sufficient. The effort in Novelty Detection has shown that sentence-level analysis is a promising research direction. However, models and theory are needed for under- standing the difference in content of the target sentences. In this paper, an argument for using current state-of-the-art in Relation and Opinion Extraction at the sentence level is made. After presenting some ideas for the use of the above technology for document retrieval, advanced extraction models are briefly described.