Search Results - (( user classification based algorithm ) OR ( java location based algorithm ))

An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

“…Differing from other complex and difficult classification models, rules-based classification algorithms produce models which are understandable for users. …”
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Automatic email classification system / Phang Siew Ting by Phang , Siew Ting

“…Automatic Email Classification System is an email reader tool that implements machine learning algorithm in email classification, manipulated by a Graphical User Interface. …”
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Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi by Rahimi, Ahmad Faris

“…The second one is to develop prototype for classification of credit cardholder behavior based on k Nearest Neighbors Algorithm. …”
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A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

Jogging activity recognition using k-NN algorithm by Afifah Ismail

“…Jogging activity recognition using the k-NN algorithm is a system that can help users collect information data of user speed movement using speed sensor and give the classification of jogging activity to the user. …”
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A review on classifying and prioritizing user review-based software requirements by Salleh, Amran, Said, Mar Yah, Osman, Mohd Hafeez, Hassan, Sa’Adah

“…This study highlights the need for better tools to handle complex user reviews. Investigating the potential of emerging machine learning models and algorithms to improve classification and prioritization accuracy is crucial. …”
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A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

“…Every day, more and more malicious mobile applications (apps) with the botnet capability have been developed to exploit end users' smartphones. Therefore, this paper presents a new mobile botnet classification based on permission and Application Programming Interface (API) calls in the smartphone. …”

A new classification model for online predicting users' future movements by Jalali, Mehrdad, Mustapha, Norwati, Mamat, Ali, Sulaiman, Md. Nasir

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Adaptive method to improve web recommendation system for anonymous users by Almurtadha, Yahya Mohammed

“…This research focuses on improving the prediction of the next visited web pages and introduces them to current anonymous user. An enhanced classification algorithm is used to assign the current anonymous user to the best web navigation profile. …”
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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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ABC: android botnet classification using feature selection and classification algorithms by Abdullah, Zubaile, Mohd Saudi, Madihah, Anuar, Nor Badrul

“…In this paper, a new approach for Android botnet classification based on features selection and classification algorithms is proposed. …”
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Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

“…Future development can be carried out by creating a database based on the user’s standard of measure and accessing it whenever the user starts the program.…”
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Maldroid- attribute selection analysis for malware classification by Rahiwan Nazar, Romli, Mohamad Fadli, Zolkipli, Mohd Zamri, Osman

“…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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Review of the machine learning methods in the classification of phishing attack by Jupin, John Arthur, Sutikno, Tole, Mohd Arfian, Ismail, Mohd Saberi, Mohamad, Shahreen, Kasim, Deris, Stiawan

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Security alert framework using dynamic tweet-based features for phishing detection on twitter by Liew, Seow Wooi

“…This model is then embedded into the detection algorithm together with the inclusion of dynamic tweet-based features which are not as part of the features used to train a classification model for phishing tweet detection. …”
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An internet of things based for smart recycle waste classification / Akmal Md Nasir by Md Nasir, Akmal

“…With a high accuracy rate for waste classification, the ResNet algorithm proved to be effective. …”
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Enhance key generation algorithm based user string identity as public key by Norhidayah, Muhammad

“…This study aims to enhance a previous algorithm called the Tripathi algorithm. The Tripathi algorithm proposes an RSA based approach to generate cryptographic keys using a user’s identity, such as an E-mail address. …”
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Development of mobile location based notification for crime cases tracking as an alternative alert for public safety / Noraini Ismail by Ismail, Noraini

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Android Mobile Malware Classification Based on System Call and Permission Using Tokenization by Intan Nurfarahin Binti Ahmad

Group formation using genetic algorithm by Che Ani, Zhamri, Husin, Mohd Zabidin, Yasin, Azman

“…However, due to lack of programming skills especially in Java programming language and the inability to have meetings frequently among the group members,most of the students’ software project cannot be delivered successfully.To solve this problem, systematic group formation is one of the initial factors that should be considered to ensure that every group consists of quality individuals who are good in Java programming and also to ensure that every group member in a group are staying closer to each other.In this research, we propose a method for group formation using Genetic Algorithms, where the members for each group will be generated based on the students’ programming skill and location of residential colleges.…”
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