Research ArticleOpen accessEvery word in the titleFuzzy Swarm Based Text SummarizationMohammed Salem Binwahlan, Naomie Salim, Ladda SuanmaliProblem statement: The aim of automatic text summarization systems is to select the most relevant information from an abundance of text sources. A daily rapid growth of data on the internet makes the achieve events of such aim a big challenge. Approach: In this study, we incorporated fuzzy logic with swarm intelligence; so that risks, uncertainty, ambiguity and imprecise values … …Journal of Computer Science, Vol. 5, Issue 5 · 30 May 2009 · 7,412 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Arabic Text-To-Speech System Based on Artificial Neural NetworksGhadeer Al-Said, Moussa AbdallahProblem statement: With the rapid advancement in information technology and communications, computer systems increasingly offer the users the opportunity to interact with information through speech. The interest in speech synthesis and in building voices is increasing. Worldwide, speech synthesizers have been developed for many popular languages English, Spanish and French and many researches and developments have been applied to those … …Journal of Computer Science, Vol. 5, Issue 3 · 31 Mar 2009 · 7,368 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleParsing Arabic Texts Using Rhetorical Structure TheoryH. I. Mathkour, A. A. Touir, W. A. Al-SaneaProblem Statement: Processing texts based on rhetorical structure theory has shown interesting results. Rhetorical Structure Theory (RST) improves the ability of extracting the semantic behind the processed text. Different applications such as information retrieval, text summarization, and text generation have proved to give better result using RST. The applicability of RST to process and understand texts has been studied in … …Journal of Computer Science, Vol. 4, Issue 9 · 30 Sep 2008 · 7,389 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleImplementation of Phonetic Context Variable Length Unit Selection Module for Malay Text to SpeechTian-Swee Tan, Sh-HussainProblem statement: The main problem with current Malay Text-To-Speech (MTTS) synthesis system is the poor quality of the generated speech sound due to the inability of traditional TTS system to provide multiple choices of unit for generating more accurate synthesized speech. Approach: This study proposes a phonetic context variable length unit selection MTTS system that is capable of providing more … …Journal of Computer Science, Vol. 4, Issue 7 · 31 Jul 2008 · 6,775 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleChi Square Feature Extraction Based Svms Arabic Language Text Categorization SystemAbdelwadood Moh’d A MESLEHThis paper aims to implement a Support Vector Machines (SVMs) based text classification system for Arabic language articles. This classifier uses CHI square method as a feature selection method in the pre-processing step of the Text Classification system design procedure. Comparing to other classification methods, our system shows a high classification effectiveness for Arabic data set in term of F-measure … …Journal of Computer Science, Vol. 3, Issue 6 · 30 Jun 2007 · 11,057 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Different Text Attack Algorithm in Integer Factoring Based SchemesMohammed A. AL-Fayoumi, Sattar J. Aboud, Musbah M. AqelText attack in integer factoring based schemes is generally calculated as an intrinsic characteristic of its symmetric attack. In this article, we illustrate that asymmetric integer factoring based schemes are also vulnerable to a text attack. Also, we show that a single message is required to increase a successful text attack versus the Lucas scheme. …Journal of Computer Science, Vol. 3, Issue 6 · 30 Jun 2007 · 6,654 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA New Text Mining Approach for Finding Protein-to-Disease AssociationsHisham Al-Mubaid, Rajit K. SinghDiscovering significant relationships between biological entities from text documents is an important task for biologists in order to develop biological models for research and discovery, especially with the existing gigantic amounts of biomedical documents and the rate at which they are increasing everyday. We propose a new text mining method to extract associations between biological entities from text documents; and … …American Journal of Biochemistry and Biotechnology, Vol. 1, Issue 3 · 30 Sep 2005 · 7,012 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Methodology to Segment the Text for Index TermsMuhammad Shoaib, Abad Ali ShahThe problem of information overload is a hot issue with the growth of the world wide web. The need for the tools those should be able to absorb this huge information and eliminate this problem is evident especially for IR systems. Text is not a simple sequence of words but carries a structure. It is essential to handle these uncontrollable … …American Journal of Applied Sciences, Vol. 2, Issue 9 · 30 Sep 2005 · 6,691 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleInvestigating Text Input Methods for Mobile PhonesBarry O, Kevin Curran, Derek WoodsHuman Computer Interaction is a primary factor in the success or failure of any device but if an objective view is taken of the current mobile phone market you would be forgiven for thinking usability was secondary to aesthetics. Many phone manufacturers modify the design of phones to be different than the competition and to target fashion trends, usually at … …Journal of Computer Science, Vol. 1, Issue 2 · 30 Jun 2005 · 7,958 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHybrid Deep Learning Model for Evaluating Subjective Answers Based on Semantic Textual SimilaritySiddhesh Kudtarkar, Kavita ShirsatSubjective answer evaluation requires accurately identifying semantic similarities between student and reference responses. This study introduces a Hybrid Deep Learning Model (HDLM) that integrates CNN, GRU, and LSTM architectures to assess Semantic Textual Similarity (STS) more effectively. The HDLM employs two parallel branches-CNN-GRU and CNN-LSTM to capture both local syntactic features and long-range contextual dependencies, followed by Manhattan distance for … …Journal of Computer Science, Vol. 22, Issue 4 · 7 Apr 2026 · 1,690 accessesView PDFCite