Adaptive, Multilingual Named Entity Recognition in Web Pages

Georgios Petasis, Vangelis Karkaletsis, Claire Grover, Ben Hachey, Maria Teresa Pazienza, Michele Vindigni, José Coch

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Most of the information on the Web today is in the form of HTML documents, which are designed for presentation purposes and not for machine understanding and reasoning. Existing web extraction systems require a lot of human involvement for maintenance due to changes to targeted web sites and for adaptation to new web sites or even to new domains. This paper presents the adaptive, multilingual named entity recognition and classification (NERC) technologies developed for processing web pages in the context of the R&D project CROSSMARC. The evaluation results demonstrate the viability of our approach
Original languageEnglish
Title of host publicationProceedings of the 16th Eureopean Conference on Artificial Intelligence, ECAI'2004, including Prestigious Applicants of Intelligent Systems, PAIS 2004, Valencia, Spain, August 22-27, 2004
Pages1073-1074
Number of pages2
DOIs
Publication statusPublished - 2004

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