9 results for “data summarization”

Set a search alert

Research ArticleOpen accessPhrase in the titleBioDARA: Data Summarization Approach to Extracting Bio-Medical Structuring InformationChung Seng Kheau, Rayner Alfred, Joe Henry ObitProblem statement: Due to the ever growing amount of biomedical datasets stored in multiple tables, Information Extraction (IE) from these datasets is increasingly recognized as one of the crucial technologies in bioinformatics. However, for IE to be practically applicable, adaptability of a system is crucial, considering extremely diverse demands in biomedical IE application. One should be able to extract a … …Journal of Computer Science, Vol. 7, Issue 12 · 24 Oct 2011 · 7,936 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsOptimizing Feature Construction Process for Dynamic Aggregation of Relational AttributesRayner AlfredProblem statement: The importance of input representation has been recognized already in machine learning. Feature construction is one of the methods used to generate relevant features for learning data. This study addressed the question whether or not the descriptive accuracy of the DARA algorithm benefits from the feature construction process. In other words, this paper discusses the application of genetic … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,929 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsAn On-line Analytical Processing (OLAP) Aggregation Function for Rising Aspects in Collaboration and Social NetworksWaqas Nawaz, Kifayat Ullah Khan, Muhammad Shoaib SiddiquiThe overwhelming usage of social and collaboration networks provides the opportunity to analyze evolution of relationships among individuals, like celebrities or co-authors. Discovering such phenomenon in large complex networks is non-trivial due to their large sizes. In this situation, the aggregation functions used in OLAP, are useful to analyze the summarized data. OLAP has successfully proven its worth on multidimensional … …Journal of Computer Science, Vol. 16, Issue 6 · 10 Jun 2020 · 7,120 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAbstractive Summarization of Long Educational Transcripts in the Era of GenAIDeepa Fernandes, Rupali Sunil WaghThe surge in online video data presents the imperative requirement of summarizing it for information compression, efficient understanding, and to support decision-making. Recent research studies have predominantly utilized structured input data for summarization. This paper explores the current state-of-the-art models in summarizing unstructured, conversational, and long transcript data. We further apply a transfer learning approach using a fine-tuned BART model, … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 403 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Deep Learning Approach for Telugu Domain Identification with Multichannel LSTM-CNNBuddha Hari Kumar, Chitra Perumal, Inakoti Ramesh Raja et al.The vast growth of textual data has ushered into the limelight, a plethora of applications in information retrieval and natural language processing (NLP). Proper extraction of information from text is heavily dependent on recognizing the thematic content, which becomes crucial in the tasks of document summarization, information extraction, question answering, machine translation, and sentiment analysis. The great complexity of this … …Journal of Computer Science, Vol. 21, Issue 9 · 26 Nov 2025 · 2,395 accessesView PDF Cite

Research ArticleOpen accessIn the abstractARABIC PART OF SPEECH TAGGING USING K-NEAREST NEIGHBOUR AND NAIVE BAYES CLASSIFIERS COMBINATIONRund Mahafdah, Nazlia Omar, Omaia Al-OmariPart Of Speech (POS) tagging forms the important preprocessing step in many of the natural language processing applications such as text summarization, question answering and information retrieval system. It is the process of classifying every word in a given context to its appropriate part of speech. Different POS tagging techniques in the literature have been developed and experimented. Currently, it … …Journal of Computer Science, Vol. 10, Issue 9 · 2 May 2014 · 7,578 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAN APPROACH FOR TEXT SUMMARIZATION USING DEEP LEARNING ALGORITHMG. PadmaPriya, K. DuraiswamyNow days many research is going on for text summarization. Because of increasing information in the internet, these kind of research are gaining more and more attention among the researchers. Extractive text summarization generates a brief summary by extracting proper set of sentences from a document or multiple documents by deep learning. The whole concept is to reduce or minimize … …Journal of Computer Science, Vol. 10, Issue 1 · 7 Nov 2013 · 7,803 accessesView PDF Cite

Research ArticleOpen accessIn the abstractDiscretization Numerical Data for Relational Data with One-to-Many RelationsRayner AlfredProblem statement: Handling numerical data stored in a relational database has been performed differently from handling those numerical data stored in a single table due to the multiple occurrences (one-to-many association) of an individual record in the non-target table and non-determinate relations between tables. Numbers in Multi-Relational Data Mining (MRDM) were often discretized, after considering the schema of the relational … …Journal of Computer Science, Vol. 5, Issue 7 · 31 Jul 2009 · 7,030 accessesView PDF Cite

Research ArticleOpen accessIn the abstractFuzzy 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 PDF Cite