Semantic Relatedness Measure Using Object Properties in an Ontology
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Computing Knowledge-Based Semantic Similarity from the Web: An Application to the Biomedical Domain
KSEM '09 Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management
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In this paper, we propose two novel web-based metrics for semantic similarity computation between words. Both metrics use a web search engine in order to exploit the retrieved information for the words of interest. The first metric considers only the page counts returned by a search engine, based on the work of [1]. The second downloads a number of the top ranked documents and applies "widecontext" and "narrow-context" metrics. The proposed metrics work automatically, without consulting any human annotated knowledge resource. The metrics are compared with WordNet-based methods. The metrics' performance is evaluated in terms of correlation with respect to the pairs of the commonly used Charles - Miller dataset. The proposed "wide-context" metric achieves 71% correlation, which is the highest score achieved among the fully unsupervised metrics in the literature up to date.