Efficient Weighted Semantic Score Based on the Huffman Coding Algorithm and Knowledge Bases for Word Sequences Embedding

Nada Ben-Lhachemi and El Habib Nfaoui
Additional contact information
Nada Ben-Lhachemi: Sidi Mohamed Ben Abdellah University, Morocco
El Habib Nfaoui: LIIAN Laboratory, Sidi Mohamed Ben Abdellah University, Morocco

International Journal on Semantic Web and Information Systems (IJSWIS), 2020, vol. 16, issue 2, 126-142

Abstract: Learning text representation is forming a core for numerous natural language processing applications. Word embedding is a type of text representation that allows words with similar meaning to have similar representation. Word embedding techniques categorize semantic similarities between linguistic items based on their distributional properties in large samples of text data. Although these techniques are very efficient, handling semantic and pragmatics ambiguity with high accuracy is still a challenging research task. In this article, we propose a new feature as a semantic score which handles ambiguities between words. We use external knowledge bases and the Huffman Coding algorithm to compute this score that depicts the semantic relatedness between all fragments composing a given text. We combine this feature with word embedding methods to improve text representation. We evaluate our method on a hashtag recommendation system in Twitter where text is noisy and short. The experimental results demonstrate that, compared with state-of-the-art algorithms, our method achieves good results.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJSWIS.2020040107 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jswis0:v:16:y:2020:i:2:p:126-142

Access Statistics for this article

International Journal on Semantic Web and Information Systems (IJSWIS) is currently edited by Brij Gupta

More articles in International Journal on Semantic Web and Information Systems (IJSWIS) from IGI Global
Bibliographic data for series maintained by Journal Editor ().