Novelty Detection via Answer Updating.

摘要

The detection of new and novel information in a document stream is an important component of potential applications. This paper describes an answer updating approach to novelty detection at the sentence level. Specifically, we explore the use of question-answering techniques for novelty detection. New information is defined as new/previously unseen answers to questions representing a user's information need. A sentence is treated as novel sentence if the system believes that it may contain a previously unseen answer to the question. In our answer updating approach, there are two important steps: question formulation and new answer detection. Experiments were carried out on data from the TREC 2002 novelty track using the proposed approach. The results show that novelty detection via answer updating outperforms other novelty measures reported in the literature in terms of precision at low recall.