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Semantic similarity of ontology instances using polarity mining

Tom Narock, Lina Zhou and Victoria Yoon

Journal of the American Society for Information Science and Technology, 2013, vol. 64, issue 2, 416-427

Abstract: Semantic similarity is vital to many areas, such as information retrieval. Various methods have been proposed with a focus on comparing unstructured text documents. Several of these have been enhanced with ontology; however, they have not been applied to ontology instances. With the growth in ontology instance data published online through, for example, Linked Open Data, there is an increasing need to apply semantic similarity to ontology instances. Drawing on ontology‐supported polarity mining (OSPM), we propose an algorithm that enhances the computation of semantic similarity with polarity mining techniques. The algorithm is evaluated with online customer review data. The experimental results show that the proposed algorithm outperforms the baseline algorithm in multiple settings.

Date: 2013
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https://doi.org/10.1002/asi.22769

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Persistent link: https://EconPapers.repec.org/RePEc:bla:jamist:v:64:y:2013:i:2:p:416-427

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https://doi.org/10.1002/(ISSN)1532-2890

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