Tech Report

ESpotter: Adaptive Named Entity Recognition for Web Browsing

Web users are facing information overload problems, i.e., it is

hard for them to find desired information on the web. Hence the

growing interest in named entity recognition (NER) for

discovering relevant information on users behalf. We present a

browser plug-in called ESpotter which adapts lexicons and

patterns to a domain hierarchy consisting of domains on the web

and user preferences for accurate and efficient NER. Mappings

are created from domain independent types to domain specific

types. Entities are highlighted according to their types, and users

are assisted by navigational functionalities between these

highlighted entities.

ID: kmi-04-12

Date: 2004

Author(s): Jianhan Zhu, Victoria Uren, Enrico Motta

Download PDF

View By

Other Publications

Latest Seminar
Mr Antonello Meloni
Department of Mathematics and Computer Science, University of Cagliari, IT

Large Language Models for Scientific Question Answering: an Extensive Analysis of the SciQA Benchmark

Watch the live webcast


Knowledge Media Institute
The Open University
Walton Hall
Milton Keynes
United Kingdom

Tel: +44 (0)1908 653800

Fax: +44 (0)1908 653169

Email: KMi Support


If you have any comments, suggestions or general feedback regarding our website, please email us at the address below.

Email: KMi Development Team