Information filtering of on-line news using dynamic abstract generation

With the information explosion from the Internet, there is a need to efficiently determine the relevance of information. This paper discusses an approach to information filtering using dynamic abstract generation techniques. Different abstract generation techniques such as the location method, indicative-phrases, keyword frequency, and title-keyword method are incorporated into a retrieval interface for on-line news articles. During news retrieval, abstract generation, an extract containing a set of verbatim sentences from the news article will be automatically produced. This will form an indicative abstract from which the prospective reader can then decide whether to read the full-length news article. In this way, a reader can filter out irrelevant news articles without having to review the entire article.