Research ArticleOpen accessIn the abstractEnhancing Semantic Web Retrieval Through Ontology-Driven Feature Extraction: A Novel PropositionMeer Hazar Khan, Muhammad Imran Sharif, Mehwish Mehmood et al.Web images represent unstructured data sets which often lead to challenges when users try to locate distinct images via text-based searches on the web. Such difficulties stem from different factors, e.g., redundant image storage, irrelevant metadata tags, and incorrect associations. To overcome this issue, we propose a semantic model based on the ontology language that enables users to find images … …Journal of Computer Science, Vol. 20, Issue 5 · 23 Feb 2024 · 5,562 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnaphora Resolution in Thai EDU SegmentationAuthapon Kongwan, Siti Sakira Kamaruddin, Farzana Kabir AhmadHuman knowledge is mostly in the form of unstructured text. Text can be transcribed into various languages such as the Thai language. To extract knowledge from Thai text, natural language tasks such as word segmentation, Elementary Discourse Unit (EDU) segmentation, and anaphora resolution is the needed tasks. Some interesting phenomena such as non-referential anaphora and the ellipsis of the owner … …Journal of Computer Science, Vol. 18, Issue 4 · 5 May 2022 · 6,065 accessesView PDFCite
Research ArticleOpen accessIn the abstractMining Sports Articles using Cuckoo Search and Tabu Search with SMOTE Preprocessing TechniqueWaheeda AlmayyanSentiment analysis is one of the most popular domains for natural language text classification, crucial for improving information extraction. However, massive data availability is one of the biggest problems for opinion mining due to accuracy considerations. Selecting high discriminative features from an opinion mining database is still an ongoing research topic. This study presents a two-stage heuristic feature selection method … …Journal of Computer Science, Vol. 17, Issue 3 · 12 Mar 2021 · 6,534 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Survey on Event Detection Models for Text Data StreamsWafa Zubair AL-Dyani, Farzana Kabir Ahmad, Siti Sakira KamaruddinEvent Detection (ED) is a study area that attracts the attention of decision-makers from various disciplines in order to help them in taking the right decision. ED has been examined on various text streams like Twitter, Facebook, Emails, Blogs, Web Forums and newswires. Many ED models have been proposed in literature. In general, ED model consists of six main phases: … …Journal of Computer Science, Vol. 16, Issue 7 · 14 Jul 2020 · 7,038 accessesView PDFCite
Research ArticleOpen accessIn the abstractArabic Poetry Authorship Attribution using Machine Learning TechniquesAl-Falahi Ahmed, Ramdani Mohamed, Bellafkih MostafaIn this study, authorship attribution in Arabic poetry will be conducted to determine the authorship of a specified text after documents with recognized authorships have been allocated. This work also measures the impact performance of Naïve Bayes, Support Vector Machine and Linear discriminant analysis for Arabic poetry authorship attribution using text mining classification. Several features such as lexical features, character … …Journal of Computer Science, Vol. 15, Issue 7 · 27 Jul 2019 · 150,975 accessesView PDFCite
Review ArticleOpen accessIn the abstractMultimodal Sentiment Analysis: A Comparison StudyIntisar O. Hussien, Yahia Hasan JazyahSentiments and emotions play a pivotal role in our daily lives. They assist decision making, learning, communication and situation awareness in human environments. Sentiment analysis is mainly focused on the automatic recognition of opinions’ polarity, as positive or negative. Nowadays, sentiment analysis is replacing the old web based survey and traditional survey methods that conducted by deferent companies for finding … …Journal of Computer Science, Vol. 14, Issue 6 · 11 Jun 2018 · 9,904 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentiment Analysis of Arabic Tweets in e-LearningHamed AL-Rubaiee, Renxi Qiu, Khalid Alomar, Dayou LiIn this study, we present the design and implementation of Arabic text classification in regard to university students' opinions through different algorithms such as Support Vector Machine (SVM) and Naive Bayes (NB). The aim of the study is to develop a framework to analyse Twitter "tweets" as having negative, positive or neutral sentiments in education or, in other words, to … …Journal of Computer Science, Vol. 12, Issue 11 · 4 Feb 2017 · 9,070 accessesView PDFCite
Literature ReviewOpen accessIn the abstractAdvances in Document Clustering with Evolutionary-Based AlgorithmsSarmad Makki, Razali Yaakob, Norwati Mustapha, Hamidah IbrahimDocument clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of … …American Journal of Applied Sciences, Vol. 12, Issue 10 · 20 Oct 2015 · 7,186 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancement of Arabic Text Classification Using Semantic Relations of Arabic WordNetSuhad A. Yousif, Venus W. Samawi, Islam Elkabani, Rached ZantoutArabic text classification methods have emerged as a natural result of the existence of a massive amount of varied textual information (written in Arabic language) on the web. In most text classification processes, feature selection is crucial task since it highly affects the classification accuracy. Generally, two types of features could be used: Statistical based features and semantic and concept … …Journal of Computer Science, Vol. 11, Issue 3 · 15 Apr 2015 · 8,065 accessesView PDFCite