A new semantic relatedness measurement using WordNet features

作者：Taieb Mohamed Ali Hadj^*; Ben Aouicha Mohamed; Ben Hamadou Abdelmajid

来源：Knowledge and Information Systems, 2014, 41(2): 467-497.

DOI：10.1007/s10115-013-0672-4

• Semantic similarity
• Semantic relatedness
• WordNet
• Information content
• Gloss

Computing semantic similarity/relatedness between concepts and words is an important issue of many research fields. Information theoretic approaches exploit the notion of Information Content (IC) that provides for a concept a better understanding of its semantics. In this paper, we present a complete IC metrics survey with a critical study. Then, we propose a new intrinsic IC computing method using taxonomical features extracted from an ontology for a particular concept. This approach quantifies the subgraph formed by the concept sub-sumers using the depth and the descendents count as taxonomical parameters. In a second part, we integrate this IC metric in a newparameterized multistrategy approach formeasuring word semantic relatedness. This measure exploits the WordNet features such as the noun "is a" taxonomy, the nominalization relation allowing the use of verb "is a" taxonomy and the shared words (overlaps) in glosses. Our work has been evaluated and compared with related works using a wide set of benchmarks conceived for word semantic similarity/relatedness tasks. Obtained results show that our IC method and the new relatedness measure correlated better with human judgments than related works.

• 出版日期2014-11