CPRel: Semantic Relatedness Computation Using Wikipedia based Context Profiles

Abstract

Semantic relatedness is a well known problem with its sig- nicance ranging from computational linguistics to Natural language Processing applications. Relatedness computation is restricted by the amount of common sense and background knowledge required to relate any two terms. This paper proposes a novel model of relatedness using context prole built on features extracted from encyclopedic knowledge. Proposed research makes use of Wikipedia to represent the context of a word in the high dimensional space of Wikipedia labels. Semantic relat- edness of a word pair is then assessed by comparing their corresponding context proles based on three dierent weighting schemes using tradi- tional Cosine similarity metrics. To evaluate proposed relatedness ap- proach, three well known benchmark datasets are used and it is shown that Wikipedia article contents can be used eectively to compute term relatedness. The experiments demonstrate that the proposed approach is computationally cheap as well as eective when correlated with human judgments.