Search Results - (( java implication _ algorithm ) OR ( using users ((using algorithm) OR (learning algorithm)) ))

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

“…The proposed DetectCombined is an innovated technique that execute a protection code based on a sequence of three stages: filtration-validation-history, this technique produces a robust protection code that distinguish between safe SQL commands and malicious ones, and reinforce the memory of detection procedure by saving previous SQL attacks in special tables in the remote database, regardless of the types of users whether a general user of admin. The outcome of this study will add to the body of knowledge the most important and recent proposed solutions to mitigate SQL injection attack, in particular those based on machine learning algorithm…”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

“…GA assists in optimizing the search process and performs machine learning. Within the GA, nearest neighbor algorithm is used in determining the most similar recorded case that can be used in solving the new case. …”

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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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

“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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Phishing attack detection using machine learning method by Jupin, John Arthur

“…This spam message includes the email and the SMS message that received by the user. There are several algorithms that can be used in the machine learning method to prevent the both attacks. …”
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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

“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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E-history Malaysian secondary school textbook using TF-IDF algorithm and text visualization / Nur Hafizah Mohd Ridzuan by Mohd Ridzuan, Nur Hafizah

“…History is one of the school subjects in Malaysian schools and known as a compulsory subject that is required to pass the SPM examination. One of the main learning methods in Malaysian education is by using textbooks as it is a universal formal school learning material and a dominant resource of learning. …”
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Behaviour Analysis Among Adolescents And Children For Cyberbullying Based On Twitter And Kaggle Dataset by Afiefah Hannani, Abdul Halim

“…Therefore, cyberbullying detection using a Machine Learning approach is suggested. This study presents the comparison of three Machine Learning algorithms for the detection using cyberbullying activity on social media platforms specifically Twitter. …”
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Estimating Depressive Tendencies Of Twitter User Via Social Media Data by Loh, Hooi Teng

“…We will use these three machine learning algorithms to compare the accuracy and performance of the depressed twitter user. …”
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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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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

“…Due to this, this paper predicts user’s future trajectory from past trajectory utilizing deep learning (DL) algorithms which are Long-Short Term Memory (LSTM), BiDirectional LSTM, and Gated Recurrent Unit (GRU). …”
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User song preferences using preference learning in artificial intelligence by Goh, Beng Jun

“…The most common model is popularity-based model because it is simple and intuitive. That another algorithm is collaborative filtering, this algorithm aims to find similarity between users, songs, and artists. …”
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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

An adaptive HMM based approach for improving e-Learning methods by Deeb B., Hassan Z., Beseiso M.

“…This adaptive algorithm can thus be applied to any e-learning platform for optimal content delivery to its users in real-time. © 2014 IEEE.…”

Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

“…A classifier model is developed using Naive Bayes characteristics. A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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Multilingual Ontology Learning Algorithm for Emails by Beseiso M., Ahmad A.R., Ismail R., Taher M.

“…In this research, we have explained the necessity for utilizing multilingual ontology learning processes to solve this problem. We have proposed the multilingual ontology learning algorithm for semantic email. …”

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

“…There are several algorithms that can be used in the machine learning method to prevent these attacks. …”
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Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster by Wan Maseri, Wan Mohd, Beg, Abul Hashem, Tutut, Herawan, K., F.Rabbi

“…K-Means is one of the unsupervised learning and partitioning clustering algorithms. It is very popular and widely used for its simplicity and fastness. …”
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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. …”

Development of machine learning-based algorithm to determine the condition in transformer oil by Mohsen Al-Katheri, Hussein Hasan

“…Classification learning app used to train DGA data divided into three categories fault, Not determined (N/D) and stray gassing. …”
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