Sinhala Short Sentence Similarity Calculation using Corpus-Based and Knowledge-Based Similarity Measures

Jcs Kadupitiya, Surangika Ranathunga, Gihan Dias


Abstract
Currently, corpus based-similarity, string-based similarity, and knowledge-based similarity techniques are used to compare short phrases. However, no work has been conducted on the similarity of phrases in Sinhala language. In this paper, we present a hybrid methodology to compute the similarity between two Sinhala sentences using a Semantic Similarity Measurement technique (corpus-based similarity measurement plus knowledge-based similarity measurement) that makes use of word order information. Since Sinhala WordNet is still under construction, we used lexical resources in performing this semantic similarity calculation. Evaluation using 4000 sentence pairs yielded an average MSE of 0.145 and a Pearson correla-tion factor of 0.832.
Anthology ID:
W16-3705
Volume:
Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016)
Month:
December
Year:
2016
Address:
Osaka, Japan
Venues:
WS | WSSANLP
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
44–53
Language:
URL:
https://aclanthology.org/W16-3705
DOI:
Bibkey:
Cite (ACL):
Jcs Kadupitiya, Surangika Ranathunga, and Gihan Dias. 2016. Sinhala Short Sentence Similarity Calculation using Corpus-Based and Knowledge-Based Similarity Measures. In Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016), pages 44–53, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Sinhala Short Sentence Similarity Calculation using Corpus-Based and Knowledge-Based Similarity Measures (Kadupitiya et al., 2016)
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PDF:
https://aclanthology.org/W16-3705.pdf