Semantic Relatedness Metric for Wikipedia Concepts Based on Link Analysis and its Application to Word Sense Disambiguation
, and .
(2008)

Wikipedia has grown into a high quality up-todate knowledge base and can enable many knowledge-based applications, which rely on semantic information. One of the most general and quite powerful semantic tools is a measure of semantic relatedness between concepts. Moreover, the ability to efficiently produce a list of ranked similar concepts for a given concept is very important for a wide range of applications. We propose to use a simple measure of similarity between Wikipedia concepts, based on Dice’s measure, and provide very efficient heuristic methods to compute top k ranking results. Furthermore, since our heuristics are based on statistical properties of scale-free networks, we show that these heuristics are applicable to other complex ontologies. Finally, in order to evaluate the measure, we have used it to solve the problem of word-sense disambiguation. Our approach to word sense disambiguation is based solely on the similarity measure and produces results with high accuracy. 1
  • @dbenz
  • @dblp
  • @psinger
This publication has not been reviewed yet.

rating distribution
average user rating0.0 out of 5.0 based on 0 reviews
    Please log in to take part in the discussion (add own reviews or comments).