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Sentiment analysis : an enhancement of ontological-based using hybrid machine learning techniques

With the fast development of World Wide Web 2.0 has resulted in huge number of reviews where the consumers share their opinion about a variety of products in the websites, forum and social media such as Twitter and Instagram. For the organizations, they have to analyze customer’s behavior to find ne...

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Main Authors: Muhammad Iqbal Abu Latiffi,, Mohd Ridzwan Yaakub,
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2018
Online Access:http://journalarticle.ukm.my/17765/1/05.pdf
http://journalarticle.ukm.my/17765/
https://www.ukm.my/apjitm/articles-year.php
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spelling my-ukm.journal.177652021-12-24T08:48:46Z http://journalarticle.ukm.my/17765/ Sentiment analysis : an enhancement of ontological-based using hybrid machine learning techniques Muhammad Iqbal Abu Latiffi, Mohd Ridzwan Yaakub, With the fast development of World Wide Web 2.0 has resulted in huge number of reviews where the consumers share their opinion about a variety of products in the websites, forum and social media such as Twitter and Instagram. For the organizations, they have to analyze customer’s behavior to find new market trends and insights. Sentiment analysis concept used to extract the positive, negative or neutral sentiment of the features from the unstructured data of product reviews. In this paper, we explore the techniques and tools used to enhance the ontology-based approach. Combination of ontology-based on Formal Concept Analysis (FCA) which a process of obtaining a formal ontology or a concept hierarchy from a group of objects with their properties and K-Nearest Neighbor (KNN) to classify the reviews. We believe with these techniques, we are able to view the strength and weakness of the product in more detail where the feature selection process will more be systematic and will result in the highest feature set. Penerbit Universiti Kebangsaan Malaysia 2018-12 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/17765/1/05.pdf Muhammad Iqbal Abu Latiffi, and Mohd Ridzwan Yaakub, (2018) Sentiment analysis : an enhancement of ontological-based using hybrid machine learning techniques. Asia-Pacific Journal of Information Technology and Multimedia, 7 (2). pp. 61-69. ISSN 2289-2192 https://www.ukm.my/apjitm/articles-year.php
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description With the fast development of World Wide Web 2.0 has resulted in huge number of reviews where the consumers share their opinion about a variety of products in the websites, forum and social media such as Twitter and Instagram. For the organizations, they have to analyze customer’s behavior to find new market trends and insights. Sentiment analysis concept used to extract the positive, negative or neutral sentiment of the features from the unstructured data of product reviews. In this paper, we explore the techniques and tools used to enhance the ontology-based approach. Combination of ontology-based on Formal Concept Analysis (FCA) which a process of obtaining a formal ontology or a concept hierarchy from a group of objects with their properties and K-Nearest Neighbor (KNN) to classify the reviews. We believe with these techniques, we are able to view the strength and weakness of the product in more detail where the feature selection process will more be systematic and will result in the highest feature set.
format Article
author Muhammad Iqbal Abu Latiffi,
Mohd Ridzwan Yaakub,
spellingShingle Muhammad Iqbal Abu Latiffi,
Mohd Ridzwan Yaakub,
Sentiment analysis : an enhancement of ontological-based using hybrid machine learning techniques
author_facet Muhammad Iqbal Abu Latiffi,
Mohd Ridzwan Yaakub,
author_sort Muhammad Iqbal Abu Latiffi,
title Sentiment analysis : an enhancement of ontological-based using hybrid machine learning techniques
title_short Sentiment analysis : an enhancement of ontological-based using hybrid machine learning techniques
title_full Sentiment analysis : an enhancement of ontological-based using hybrid machine learning techniques
title_fullStr Sentiment analysis : an enhancement of ontological-based using hybrid machine learning techniques
title_full_unstemmed Sentiment analysis : an enhancement of ontological-based using hybrid machine learning techniques
title_sort sentiment analysis : an enhancement of ontological-based using hybrid machine learning techniques
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2018
url http://journalarticle.ukm.my/17765/1/05.pdf
http://journalarticle.ukm.my/17765/
https://www.ukm.my/apjitm/articles-year.php
_version_ 1720437888091422720
score 13.211869

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