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2020-02-27T00:15:41+00:00
Semantic relatedness metric for Wikipedia concepts based on link analysis and its application to word sense disambiguation
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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.
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Cross-sectional
We have presented a simple measure of semantic relatedness, based on the link structure of Wikipedia. We addressed the problem of computing this measure efficiently and have provided heuristics for computing
top k related articles. These heuristics achieve high accuracy, but limit the search space drastically and make the approach suitable for practical use in a variety of data intensive systems. We also presented a
randomized algorithm to compute the relatedness measure between two articles efficiently and shown that its accuracy in ranking is very close to the true measure. In order to evaluate the quality of the measure, we have presented a simple method for word sense disambiguation, based on the relatedness measure. We evaluated our approach and found it to perform on par with the competing approaches and close to the performance of human experts.
Experiment responses
Wikipedia pages
Yes
Conference paper
Experiment
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
10942
Undetermined
Design and action
Semantic relatedness metric for Wikipedia concepts based on link analysis and its application to word sense disambiguation
Article
Main topic
Live Wikipedia
Not specified
Article
2008Z
2454466.5
2012-03-15T20:30:09Z
2456002.35427
2014-01-30T20:31:21Z
2456688.3551
Semantic relatedness metric for Wikipedia concepts based on link analysis and its application to word sense disambiguation