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Tech Report kmi-04-12 Abstract


ESpotter: Adaptive Named Entity Recognition for Web Browsing
Techreport ID: kmi-04-12
Date: 2004
Author(s): Jianhan Zhu, Victoria Uren, Enrico Motta
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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.
 
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Social Software is...


Social Software
Social Software can be thought of as "software which extends, or derives added value from, human social behaviour - message boards, musical taste-sharing, photo-sharing, instant messaging, mailing lists, social networking."

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.