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 |
Available under License Creative Commons: Attribution International Public License 4.0.
Download (355kB) | Preview
Export
Downloads
Downloads per month over past year