Search Results - (( _ applications learning algorithms ) OR ( web application using algorithm ))*

Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

“…This system is achieved using the Genetic Algorithm which is capable of performing information retrieval and learning algorithm. …”
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Web Usage Mining for UUM Learning Care Using Association Rules by Azizul Azhar, Ramli

“…E-Learning is one of the Web based application where it will facing with large amount of data. …”
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Web usage mining for UUM learning care using association rules by Ramli, Azizul Azhar

“…Application of data milling techniques to the World Wide Web referred as Web mining where this term has been used in three distinct ways; Web Content Mining, Web Structure Mining and Web Usage Mining. …”
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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. …”
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Intelligent cooperative web caching policies for media objects based on decision tree supervised machine learning algorithm by Ibrahim, Hamidah, Yasin, Waheed, Abdul Hamid, Nor Asilah Wati, Udzir, Nur Izura

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Car dealership web application by Yap, Jheng Khin

“…The used car dealership web application was implemented with ASP.NET Core. …”
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Multilingual Ontology Learning Algorithm for Emails by Beseiso M., Ahmad A.R., Ismail R., Taher M.

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Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

“…The results will help with real-world data mining applications of machine learning and be a useful guide for further study and practical applications.…”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…This project is developed by using Rapid Application Development methodology as it is the model that is most suitable for developing this web tools. …”
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Target heart rate zone detector during exercise based on real-time facial expression using single shot detection algorithm / Muhammad Azziq Shamsudin, Raihah Aminuddin and Ummu Mar... by Shamsudin, Muhammad Azziq, Aminuddin, Raihah, Abdul Jalil, Ummu Mardhiah

“…The object detection machine learning model used in this project is Single Shot Detector (SSD) algorithm. …”
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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.…”
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Bot detection using machine learning algorithms on social media platforms by Gannarapu, Sainath, Dawoud, Ahmed, Ali, Rasha S., Alwan, Ali Amer

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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

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Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

“…The proposed security architecture is constructed as an adaptive way-forward Internet-of-Things (IoT) friendly security solution that is comprised of three cyclic parts: learn, predict and prevent. A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

“…The proposed security architecture is constructed as an adaptive way-forward Internet-of-Things (IoT) friendly security solution that is comprised of three cyclic parts: learn, predict and prevent. A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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A WEB-BASED SYSTEM FOR THE PREDICTION OF STUDENT PERFORMANCE IN UPCOMING PUBLIC EXAMS BASED ON ACADEMIC RECORDS by DELLON, NELSON BRUNNIE

“…Teachers will be able to precisely forecast their students' impending grades utilizing the system's web-based application integration and machine learning algorithms. …”
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A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. The experimental result shows that the Random Forest Algorithm has achieved the highest detection accuracy of 99.4% with the lowest false positive rate of 16.1% as compared to other machine learning algorithms. …”

Fake news detection: A machine learning approach by Yeoh, Dennis Guan Lee

“…These models were evaluated in order to pick one to be deployed to the web application. The final model chosen to be deployed was a model trained using a Multinomial Naïve Bayes algorithm.…”
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Defect green coffee bean detection using image recognition and supervised learning by Shafian Izan Sofian

“…Therefore, in this research project, the process will be conducted by using an image classifier with the model of a machine learning algorithm which the candidates comprise of Support Vector Machine, k-Nearest Neighbour and Decision Tree. k-nearest neighbour has the highest F1-score (0.51) than the other two algorithms (Support Vector Machine: 0.50, and Decision Tree: 0.48). …”
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Brain tumor image segmentation using deep learning approach by Darshan, Suresh

“…Deep learning algorithm is able to provide good tumor segmentation results compared to other conventional segmentation algorithms as it learns from the labeled brain MRIs to predict the location of tumor region and consequently segment the tumor. …”
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