Search Results - (( _ applications ((acs algorithm) OR (bayes algorithm)) ) OR ( web application based algorithm ))*

Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging by Olanrewaju, Rashidah Funke, Al-Qudah, Dua'a Mahmoud Mohammad, Azman, Amelia Wong, Yaacob, Mashkuri

Get full text
Get full text
Get full text

A Data Mining Approach to Construct Graduates Employability Model in Malaysia by Myzatul Akmam Sapaat, Aida Mustapha, Johanna Ahmad, Khadijah Chamili, Rahamirzam Muhamad

Get full text

Applying learning to filter text by Sainin, Mohd Shamrie

“…Text filtering has been a successful application especially in e-mail filtering. The use of probabilistic approaches such as naïve Bayes algorithm is the effective algorithms currently known for learning to filter or classify text document.Naïve Bayes algorithm is one of the algorithms in Machine Learning that manipulates probability estimation or reasoning about the observed data.The growing of bulk e-mail or known as spam e-mail becomes a threat to users’ privacy and network load and in the case of e -mail filtering,naïve Bayes classifier can be trained to automatically detect spam messages.Similar to the e-mail, forum application may be misused by the user to send bad messages and in some extent may offence other readers.Forum filtering may be less important compared to e-mail spam filtering; however there is a possibility of using naïve Bayes to learn the messages and automatically detect bad messages.Most of the forum application found in the web is applying keyword based text filtering which scan the words and change the detected words into certain representation.Instead of defining a set of keywords to filter the forum messages, this paper will explains the experiment in applying a learning to filter text especially in the educational and anonymous forum message, where there is no user registration required to submit messages.…”
Get full text
Get full text

A data mining approach to construct graduates employability model in Malaysia by Sapaat, Myzatul Akmam, Mustapha, Aida, Ahmad, Johanna, Chamili, Khadijah, Muhamad, Rahamirzam

Get full text
Get full text
Get full text

Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Yasin, Waheed, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

Get full text
Get full text
Get full text

Cyberbullying detection: a machine learning approach by Yeong, Su Yen

“…Machine learning is a hot topic and it is widely implemented in software, web application and more. Those algorithms are used in the classification or regression model to predict an input. …”
Get full text
Get full text

An Automated System For Classifying Conference Papers by Ngan, Seon Choon Han

Get full text
Get full text

An efficient fuzzy clustering algorithm for mining user session clusters on web log data by Mallik, M. A., Zulkurnain, Nurul Fariza

Get full text
Get full text
Get full text
Get full text

Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
Get full text
Get full text
Get full text

A malicious URLs detection system using optimization and machine learning classifiers by Lee, Ong Vienna, Heryanto, Ahmad, Mohd Faizal, Ab Razak, Anis Farihan, Mat Raffei, Eh Phon, Danakorn Nincarean, Shahreen, Kasim, Sutikno, Tole

“…In this study, we applied features optimization approaches by using a bio-inspired algorithm for selecting significant URL features which able to detect malicious URLs applications. …”
Get full text
Get full text
Get full text

Banana recognition system using convolutional neural network / Mohamad Shafiq Rosli by Rosli, Mohamad Shafiq

“…There are many machines learning types and classification techniques have widely used nowadays such as Support Vector Machine, K-Nearest Neighbors, Neural Network and Naïve-Bayes Classifier are defined and studied. The design and implementation of web-based application will also be stated to state the working progress for the final year project. …”
Get full text
Get full text

An efficient data transformation technique for web log by Madihah Mohd Saudi, Ridzuan F., Hashim H.A.-B.

Identifying suicidal ideation through twitter sentiment analysis using Naïve Bayes / Annasuha Atie Atirah Alias by Alias, Annasuha Atie Atirah

“…Thus, this project aims to design, develop, and evaluate web-based application utilizing sentiment analysis, specifically employing the Naïve Bayes algorithm, to identify and analyze suicidal ideation within Twitter posts. …”
Get full text
Get full text

Detection of SQL injection attack using machine learning by Tung, Tean Thong

“…Integrating this system into the backend of the web application server would augment the safety and security measures of the online application. …”
Get full text
Get full text

Suspicious activities detection for anti-money laundering using machine learning techniques by Lim, Aun Chir

Get full text
Get full text

Customer sentiment analysis through social media feedback by Siti Nur Syamimi, Mat Zain

“…Customer feedback data were taken from Twitter through Streaming API (Application Programming Interface), where Tweets are retrieved in real time based on search terms, time, users and likes. …”
Get full text
Get full text

Text Categorization Using Naive Bayes Algorithm by Wan Hazimah, Wan Ismail

Get full text
Get full text
Get full text

Improving malicious detection rate for Facebook application in OSN platform by Angamuthu, Laavanya

“…Therefore, to identify malicious apps, we ask the question: given a Facebook application, can we determine if it is malicious? 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. …”
Get full text
Get full text

Text categorization using naive bayes algorithm by Wan lsmail @ W. Abdullah, Wan Hazimah, Kamaruddin, Siti Sakira, Sainin, Mohd Shamrie

Get full text
Get full text

Phishing image spam classification research trends: Survey and open issues by John Abari, Ovye, Mohd Sani, Nor Fazlida, Khalid, Fatimah, Mohd Yunus Bin Sharum, Mohd Yunus, Mohd Ariffin, Noor Afiza

“…This study reviews articles on phishing image spam classification published from 2006 to 2020 based on spam classification application domains, datasets, features sets, spam classification methods, and the measurement metrics adopted in the existing studies. …”
Get full text
Get full text