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Research ArticleOpen accessEvery word in the titleTopic-Transformer for Document-Level Language UnderstandingOumaima Hourrane, El Habib BenlahmarAs long as natural language processing applications are considered prediction problems with insufficient context, usually referred to as a single sentence or paragraph, this does not reveal how humans perceive natural language. When reading a text, humans are sensitive to much more context, such as the rest or other relevant documents. This study focuses on simultaneously capturing syntax and global … …Journal of Computer Science, Vol. 18, Issue 1 · 22 Jan 2022 · 6,616 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHow to Document Computer NetworksSabah Al-Fedaghi, Bader BehbehaniDocumenting networks is an essential tool for troubleshooting network problems. The documentation details a network’s structure and context, serves as a reference and makes network management more effective. Complex network diagrams are hard to document and maintain and are not guaranteed to reflect reality. They contain many superficial icons (e.g., wall, screen and tower). Defining a single coherent network architecture … …Journal of Computer Science, Vol. 16, Issue 6 · 10 Jun 2020 · 7,584 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Multi Layer Perceptron Along with Memory Efficient Feature Extraction Approach for Bengali Document CategorizationQuazi Ishtiaque Mahmud, Noymul Islam Chowdhury, Md MasumIn terms of the total number of speakers in the world Bengali stands as the seventh language and it has been used by approximately 265 million people worldwide. Day by day more people are expressing their views and opinions in Bengali in digital platforms like blogs and social media on various topics. Despite this, very little work has been done … …Journal of Computer Science, Vol. 16, Issue 3 · 28 Mar 2020 · 7,815 accessesView PDFCite
Literature ReviewOpen accessEvery word in the titleAdvances 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 accessEvery word in the titleDocument Clustering Based on Firefly AlgorithmAthraa Jasim Mohammed, Yuhanis Yusof, Husniza HusniDocument clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters. Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization. This study explores the adaptation of another swarm algorithm which … …Journal of Computer Science, Vol. 11, Issue 3 · 26 Mar 2015 · 7,510 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEfficacious Geospatial Information Retrieval Using Density Probabilistic Document Correlation ApproachR. Uma, MuneeswaranInformation Retrieval (IR) is a profound technique to find information that addresses the need of query. Processing of normal text is easier and information can be retrieved efficiently. There are plenty of algorithms in hand to carry out the normal text retrieval. Whereas retrieving geospatial information is very complex and requires additional operations to be performed. Since geospatial data contain … …Journal of Computer Science, Vol. 9, Issue 1 · 16 Feb 2013 · 7,011 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAutomatic Multi Document Summarization ApproachesYogan Jaya Kumar, Naomie SalimProblem statement: Text summarization can be of different nature ranging from indicative summary that identifies the topics of the document to informative summary which is meant to represent the concise description of the original document, providing an idea of what the whole content of document is all about. Approach: Single document summary seems to capture both the information well but … …Journal of Computer Science, Vol. 8, Issue 1 · 1 Nov 2011 · 8,712 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleImproving the Performance of Multivariate Bernoulli Model based Documents Clustering Algorithms using Transformation TechniquesPerumal Pitchandi, Nedunchezhian RajuProblem statement: Document clustering is the most important areas of data mining since they are very much and currently the subject of significant global research since such areas strengthen the enterprises of web intelligence, web mining, web search engine design and so forth. Generative models based on the multivariate Bernoulli and multinomial distributions have been widely used for text classification. … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,281 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Study of Forms and Linguistic Usage of Meeting Documents in the Reign of His Majesty King Chulalongkorn and the Reign of His Majesty King Bhumibol AdulyadejPreeya HiranpraditProblem statement: At present, meeting is an activity which is necessary for work. Gathering for discussing or solving problems is assumed that it has been held since the reign of His Majesty King Chulalongkorn. The purposes of this research were these: (1) to investigate forms of meeting documents in the reign of His Majesty King Chulalongkorn and the reign of … …Journal of Social Sciences, Vol. 6, Issue 3 · 30 Sep 2010 · 7,455 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIntegrated Clustering and Feature Selection Scheme for Text Documents.M. Thangamani, P. ThangarajProblem statement: Text documents are the unstructured databases that contain raw data collection. The clustering techniques are used group up the text documents with reference to its similarity. Approach: The feature selection techniques were used to improve the efficiency and accuracy of clustering process. The feature selection was done by eliminate the redundant and irrelevant items from the text document … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,163 accessesView PDFCite