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KMi Seminars
ESpotter: A Domain and User Adaptation Approach for Named Entity Recognition on the Web
This event took place on Monday 14 June 2004 at 12:30

 
Jianhan Zhu

Named entity recognition (NER) systems are commonly designed with a "one-size-fits-all" philosophy. Lexicons and patterns manually crafted or learned from a training set of documents are applied to any other document without taking into account its background and user needs. However, when applying NER to Web pages, due to the diversity of these Web pages and user needs, one size frequently does not fit all. In this talk, I present a system called ESpotter, which improves NER on the Web by adapting lexicons and patterns to domains on the Web and user preferences. My results show that ESpotteqr provides more accurate and efficient NER on Web pages from various domains than current NER systems. ESpotter is implemented as a browser plug-in to help solve the information overload problem on the Web by discovering relevant information on user's behalf. Further work of integrating ESpotter with ontology based semantic browsing tool, Magpie, and the KMi semantic Web site are explored.

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KMi Seminars Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

Knowledge Management is...


Knowledge Management
Creating learning organisations hinges on managing knowledge at many levels. Knowledge can be provided by individuals or it can be created as a collective effort of a group working together towards a common goal, it can be situated as "war stories" or it can be generalised as guidelines, it can be described informally as comments in a natural language, pictures and technical drawings or it can be formalised as mathematical formulae and rules, it can be expressed explicitly or it can be tacit, embedded in the work product. The recipient of knowledge - the learner - can be an individual or a work group, professionals, university students, schoolchildren or informal communities of interest.
Our aim is to capture, analyse and organise knowledge, regardless of its origin and form and make it available to the learner when needed presented with the necessary context and in a form supporting the learning processes.