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LexMa: Tabular data to knowledge graph matching using lexical techniques

Tyagi, S. & Jimenez-Ruiz, E. ORCID: 0000-0002-9083-4599 (2020). LexMa: Tabular data to knowledge graph matching using lexical techniques. CEUR Workshop Proceedings, 2775, pp. 59-64.

Abstract

With the fundamentals of lives dependent upon the extensive use of the internet-based searches for common life items, there is an ever-growing demand of the quick and meaningful search query systems. This has given the rise of the concept called Semantic Web. There are many challenges in developing the Semantic Web however one fundamental challenge is to design systems to enable the semantic access to the information in tabular data (e.g., Web tables). In this paper, we discuss one such system which has been developed for the automatic annotation of the tabular data using a knowledge graph. We call this system LexMa. Our system is based on lexical matching techniques. LexMa has participated in the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2020).

Publication Type: Article
Additional Information: Copyright © 2020 for this paper by its authors.
Publisher Keywords: Lexical Matching, Web Tables, Cosine Similarity, SemanticTable Interpretation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Departments: School of Science & Technology > Computer Science
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