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15 results for “Content Filtering”
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Research ArticleOpen accessPhrase in the titleA Content Filtering from Spam Posts on Social Media using Weighted Multimodal ApproachChastine Fatichah, Wildan F. Lazuardi, Dini A. Navastara et al.The system for filtering spam posts on social media is preferred to obtain the relevant content and expected by users. The previous works on spam detection have been done to filter irrelevant content on email and social media based on text or image separately. Due to the social media posts are commonly in the form of image, text, or both, … …Journal of Computer Science, Vol. 17, Issue 1 · 21 Jan 2021 · 7,904 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing Bias Detection in Tweets Using Bayesian Probabilistic ModelPrasanth G Rao, Harsha Chigurupati, Krish Hashia et al.Content moderation on social media faces persistent challenges from inconsistent evaluation shaped by subjective judgment and subtle semantic variations. This work proposes a Bayesian probabilistic framework for detecting bias in tweets using WordNet-based vocabulary filtering, statistical normalization via z-scores, and threshold optimization. The system is stateless, scalable, and dataset-agnostic, requiring no session-specific information. Unlike complex models such as Support Vector … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,009 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Hybrid Machine and Deep Learning Model for Detecting Arabic Phishing EmailsFahad GhabbanPhishing emails are becoming an increasingly popular type of cybercrime on the internet, affecting both businesses and individuals. The attackers generally use various methods to trick victims and extract personal information from them, such as bank details, home addresses, and account information. Many attempts have been proposed to tackle this issue by using filtering mechanisms or automated classification methods which … …Journal of Computer Science, Vol. 22, Issue 1 · 9 Feb 2026 · 1,897 accessesView PDFCite
Review ArticleOpen accessIn the abstractWeb Scraping for Product Recommendations: A Review of Techniques and ApplicationsAmarinder Kaur, Deepak PrasharA comprehensive method for developing a reliable product recommender system leveraging sophisticated web scraping technologies, machine learning, and natural language processing techniques. The proposed system addresses key challenges in personalized product recommendation, including the difficulty of integrating diverse data from multiple e-commerce platforms, ensuring data quality, and improving recommendation accuracy to enhance user experience. Specifically, this research tackles issues related … …Journal of Computer Science, Vol. 21, Issue 6 · 21 Jun 2025 · 4,225 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenome-Wide Association Study of Single Nucleotide Polymorphisms with Milk Traits in Red Gorbatov CattleMarina Ivanovna Selionova, Grigorii Sergeyevich Shekhovtsev, Ivan Petrovich Prokhorov et al.In order to preserve the gene pool of the Red Gorbatov breed, it is necessary to use a set of genomic analysis tools that allows more efficient planning in obtaining individuals who meet the economic requirements of dairy farming. The aim of the work was to identify candidate genes associated with milk production traits in Red Gorbatov cattle using a … …American Journal of Animal and Veterinary Sciences, Vol. 19, Issue 4 · 12 Oct 2024 · 4,736 accessesView PDFCite
Research ArticleOpen accessIn the abstractCommunity Aware Recommendation System with Explicit and Implicit Link PredictionMuhammed E Abd Alkhalec Tharwat, Mohd Farhan Md Fudzee, Shahreen Kasim et al.Recommendation systems are essential tools that help users discover content they may be interested in, amidst the vast amount of information available online. However, current methods, such as using historical user-item interactions and collaborative filtering, have limitations in accurately predicting user preferences. Our research aims to address these challenges and improve the performance of recommendation systems. In this article, we … …Journal of Computer Science, Vol. 19, Issue 8 · 19 Jul 2023 · 5,858 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvSVD++: A Hybrid Deep CF Recommender Model using Convolutional Neural NetworkMohamed Grida, Lamiaa Fayed, Mohamed HassanRecommender systems are powerful systems that give added value to business and corporation. They are relatively recent technology and they will only keep improving in the future. The most widely used algorithms for recommender systems are categorized into the traditional recommender and deep-based recommender system. The traditional recommendation algorithm suffers from sparse data that significantly degrades recommendation accuracy. The hybrid … …Journal of Computer Science, Vol. 16, Issue 12 · 13 Jan 2021 · 6,731 accessesView PDFCite
Review ArticleOpen accessIn the abstractApplications of Nature-Inspired Algorithms in Different Aspects of Semantic WebDeepika Chaudhary, Jaiteg Singh, D. P. KothariNature has always inspired us all the waggle dance of Honey bee, the school of whales and the swarm of ants, each element when observed carefully has the abundance of teachings. If we carefully observe nature, we find that although Nature seems to be very simple and systematic, it hides many complexities underneath it. As technology also follows the same … …Journal of Computer Science, Vol. 14, Issue 2 · 14 Feb 2018 · 8,760 accessesView PDFCite
Research ArticleOpen accessIn the abstractEXPLOITING SOCIAL TAGS TO OVERCOME COLD START RECOMMENDATION PROBLEMA. S. Ghabayen, Shahrul Azman NoahThe practice and method of collaboratively creating and managing tags to annotate and categorize content has resulted in the creation of folksonomy. Folksonomies provide new opportunities and challenges in the field of recommender systems. Despite the considerable amount of researches done in the context of recommender systems, the specific problem of integrating tags into standard recommender system algorithms is less … …Journal of Computer Science, Vol. 10, Issue 7 · 18 Feb 2014 · 7,084 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Approach for Detecting Stego Content in Corporate Mail Using Neural Network Based Simplified-Data Encryption Standard AlgorithmP. T. Anitha, M. Rajaram, S. N. SivanandhamProblem statement: The major growth of information technology is based on the security measures implemented. Steganography is a method which is used to give high level security. Approach: Today, email management and email authenticity must be unquestionable with strong chains of custody, constant availability and tamper-proof security. A secure communication can be achieved through neural based steganography. Email is insecure. … …American Journal of Applied Sciences, Vol. 9, Issue 5 · 12 Mar 2012 · 7,128 accessesView PDFCite