Automatic keyword extraction for news finder

Newspapers are one of the most challenging domains for information retrieval systems: new articles appear everyday written in different languages, with multimedia contents and the news repositories may be updated in a matter of hours so information extraction is crucial to the metadata contents of the news. Further approaches of "smart retrieval" have to cope with multimedia and multilingual features as well as have to obtain really good precision features in order to reach a high degree of user satisfaction with the retrieved documents. The paper focus is the description of the automatic keyword extraction (AKE) process for news characterization that uses several linguistic techniques to improve the current state of the text-based information retrieval(1). The first prototype implemented focusing in the AKE process (www.omnipaper.org) is described and some relevant performance features are included. Finally, some conclusions and comments are given regarding the role of the linguistic engineering in the web era.