Sematch: Semantic similarity framework for Knowledge Graphs

Sematch is an integrated framework for the development, evaluation and application of semantic similarity for Knowledge Graphs. The framework provides a number of similarity tools and datasets, and allows users to compute semantic similarity scores of concepts, words, and entities, as well as to int...

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Bibliographic Details
Published in:Knowledge-based systems 2017-08, Vol.130, p.30-32
Main Authors: Zhu, Ganggao, Iglesias, Carlos A.
Format: Article
Language:English
Subjects:
Classification
Evaluation
Graphs
Knowledge base
Knowledge Graphs
Semantic similarity
Semantics
Similarity
Taxonomy
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Summary:Sematch is an integrated framework for the development, evaluation and application of semantic similarity for Knowledge Graphs. The framework provides a number of similarity tools and datasets, and allows users to compute semantic similarity scores of concepts, words, and entities, as well as to interact with Knowledge Graphs through SPARQL queries. Sematch focuses on knowledge-based semantic similarity that relies on structural knowledge in a given taxonomy (e.g. depth, path length, least common subsumer), and statistical information contents. Researchers can use Sematch to develop and evaluate semantic similarity metrics and exploit these metrics in applications.
ISSN:0950-7051
1872-7409
DOI:10.1016/j.knosys.2017.05.021