Search Results - (( user predictive modelling algorithm ) OR ( java implication based algorithm ))

Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media A., Abu Osman, Md. Tap

“…Findings – WiFi’s SS contributes more in accuracy to the prediction of user location than WiFi’s SQ. Moreover, the new framework based on ELM has been compared with the k-Nearest Neighbor and the results have shown that the proposed model based on the extreme learning algorithm outperforms the k-Nearest Neighbor approach. …”
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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

“…The approach is based on the using longest common subsequence algorithm to classify current user activities to predict user next movement. …”
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Predicting user trajectories using deep learning algorithms / Ahmad Zaki Aiman Abdul Rashid, Azita Laily Yusof and Norsuzila Ya’acob by Abdul Rashid, Ahmad Zaki Aiman, Yusof, Azita Laily, Ya’acob, Norsuzila

“…These conclude that LSTM model are the most suitable model for predicting user trajectories among DL algorithms. …”
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A new classification model for online predicting users' future movements by Jalali, Mehrdad, Mustapha, Norwati, Mamat, Ali, Sulaiman, Md. Nasir

“…To provide online prediction efficiently, we advance architecture for online predicting in web usage mining system by proposing novel model based on Longest Common Subsequence algorithm for classifying user navigation patterns. …”
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Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media Anugerah, Md. Tap, Abu Osman

“…Findings – WiFi's SS contributes more in accuracy to the prediction of user location than WiFi's SQ. Moreover, the new framework based on ELM has been compared with the k-Nearest Neighbor and the results have shown that the proposed model based on the extreme learning algorithm outperforms the k-Nearest Neighbor approach. …”
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A web usage mining approach based on LCS algorithm in online predicting recommendation systems by Jalali, Mehrdad, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

“…To provide online prediction efficiently, we advance an architecture for online predicting in Web Usage Mining system and propose a novel approach based on LCS algorithm for classifying user navigation patterns for predicting users' future requests. …”
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A Web-Based Recommendation System To Predict User Movements Through Web Usage Mining by Jalali, Mehrdad

“…In the online phase, the longest common subsequence algorithm is used as a new approach in recommendation system for classifying current user activities to predict user next movements. …”
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Stock indicator scanner customization tool using deep reinforcement learning by Cheong, Desmond YongHong

“…Nowadays, there have some applications provide predictive model for user to predict the stock trend, however user cannot customize the type of input data used in the predictive models. …”
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A New Algorithm For Prediction WIMAX Traffic Based On Artificial Neural Network Models by Daw Abdulsalam Ali Daw, Kamaruzzaman Bin Seman, Madihah Mohd Saudi

“…The decision of changing the ANN architecture is essentially based on prediction results to obtain the best ANN model for flow traffic prediction model. …”
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An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms by Zahid, Aafaq

“…There is a technique known as normalization which develops models like user involvement in subject matter or user likeness according to the details of item to predict ratings to user. …”
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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

“…Furthermore, longest common subsequence algorithm is used for classifying current user activities to predict user next movement. …”
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Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan by Hamdan, Ezaryf

“…The algorithm undergoes rigorous training with a vast dataset to ensure high prediction accuracy and reliability. …”
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Dynamic modeling by usage data for personalization systems by Aghabozorgi, S.R., Teh, Y.W.

“…Finally, we discuss the on-line model for user behaviour prediction in the web personalization system.…”
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Text based personality prediction from multiple social media data sources using pre-trained language model and model averaging by Christian, Hans, Suhartono, Derwin, Chowanda, Andry, Kamal Z., Zamli

“…Firstly, these algorithms take a long time to train the model owing to its sequential inputs. …”
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Prediction of Machine Failure by Using Machine Learning Algorithm by Fakhrurazi, Nur Amalina

“…Model built resulted in variables importance’s ranking and subsequently, prediction can be made. …”
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An AI Chatbot for personalized music recommendations based on user emotions / Rula M Ali Farkash and Tengku Zatul Hidayah Tengku Petra by Ali Farkash, Rula M, Tengku Petra, Tengku Zatul Hidayah

“…These results show that the models are learning effectively and can successfully recommend music based on user emotions.…”
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Stock price monitoring system by Ng, Chun Ming

“…As stock price is time series data, a time series prediction algorithm is being utilized to build a deep learning model, namely Long Short-Term Memory (LSTM). …”
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Using Markov Model and Association Rules for Web Access Prediction by Siriporn, Chimphlee, Salim, Naomie, Ngadiman, Mohd. Salihin, Witcha, Chimphlee

“…A large amount of research has been done on trying to predict correctly the pages a user will request. This task requires the development of models that can predicts a user’s next request to a web server. …”
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Adaptive-model based self-tuning generalized predictive control of a biodiesel reactor / Ho Yong Kuen by Ho, Yong Kuen

“…Traditionally, the Recursive Least Squares (RLS) algorithm was used in the Generalized Predictive Control (GPC) framework solely for model adaptation purposes. …”
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A Mobile Application For Stock Price Prediction by Choy, Yi Tou

“…The results show ARIMA has the least error among all five prediction algorithms. Therefore, ARIMA is the best prediction model to implement in the mobile application for stock price prediction. …”
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