Search Results - (( developing online intention algorithm ) OR ( java binary classification algorithm ))

An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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A recommender system approach for classifying user navigation patterns using longest common subsequence algorithm. by Jalali, Mehrdad, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

“…In this paper, to provide online predicting effectively, we develop a model for online predicting through web usage mining system and propose a novel approach for classifying user navigation patterns to predict users’ future intentions. …”
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Analysis of online CSR message authenticity on consumer purchase intention in social media on Internet platform via PSO-1DCNN algorithm by Li, Man, Liu, Fang, Abdullah, Zulhamri

“…This work proposes an algorithm based on PSO-1DCNN joint optimization to analyze the impact of online CSR information authenticity on consumers’ purchase intention in social media on the Internet platform. …”
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

“…In order to overcome this problem, a classification model for intent recognition is developed. Dataset from Kaggle which contains English reviews from Shopee is downloaded to be used for the modelling process. …”
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A Web-Based Recommendation System To Predict User Movements Through Web Usage Mining by Jalali, Mehrdad

“…The latest contribution in this area achieves about 50% for the accuracy of the recommendations. To provide online prediction effectively, this study has developed a Web based recommendation system to Predict User Movements, named as WebPUM, for online prediction through web usage mining system and proposed a novel approach for classifying user navigation patterns to predict users‘ future intentions. …”
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WebPUM : a web-based recommendation system to predict user future movements. by Jalali, Mehrdad, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

“…To effectively provide online prediction, we have developed a recommendation system called WebPUM, an action using Web usage mining system and propose a novel approach online prediction for classifying user navigation patterns to predict users’ future intentions. …”
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From AI to Experience How Personalization Shapes Online Shopping Journeys in E-Marketplaces by Raeni Dwi, Santy, Yoga, Wicaksana, Mohammad Fauzil, Adhim

“…Using the recent development of social commerce integration into e-commerce, particularly the merger of TikTok and Tokopedia, as a contextual backdrop, the research highlights how recommendation algorithms, chatbots, and personalized content contribute to consumer decision-making processes. …”
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Multivariate EEG signal processing techniques for the aid of severely disabled people by Ibrahimy, Muhammad Ibn, Ibrahimy, Ahmad Ibn

“…Two fundamental objectives for BCI based on motor movement imagery from multichannel signals are aimed at in this research work: i) to develop a technique of multivariate feature extraction for motor imagery related to multichannel EEG signals; and ii) to develop an appropriate machine learning based feature classification algorithm for Brain Computer Interface. …”
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Improving malicious detection rate for Facebook application in OSN platform by Angamuthu, Laavanya

“…Our key contribution in this part is in developing malware detection in Facebook third party application by using Naïve Bayes algorithm technique .We identify a set of features that help us distinguish malicious apps from benign ones. …”
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Loss minimization DTC electric motor drive system based on adaptive ANN strategy by Yonis M Yonis, Buswig, Sim, Sy Yi, Wahyu, Mulyo Utomo, Goh, Hui Hwang, Chien, Siong Kai, Alvin, John Lim Meng Siang, Nor Aira, Zambri, Kah, Haw Law, Sim, Gia Yi

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Trends on technologies and artificial intelligence in education for personalized learning: systematic literature review by Hashim, Suraya, Omar, Muhd Khaizer, Ab. Jalil, Habibah, Mohd Sharef, Nurfadhlina

“…Based on the findings, most learning elements, such as technology, teaching approach, teaching content can be adapted to each student's needs and learning intent in personalized learning. Personalised learning using AI is an approach that focuses on generating training to match the specific needs of each student such as in adaptive learning, online learning, MOOCs, and many other technologies. …”
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