Search Results - (( java implementation means algorithm ) OR ( using message learning algorithm ))

Learning to Filter Text in Forum Malay Message using Naive Bayesian Technique by Ab. Halim, Norhadila

“…The paper explains about me use of the basic naive Bayesian algorithm to classify forum messages whether clean or bad where clean message has no bad words, while bad message contains at least one bad word. …”
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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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Implementation of hashed cryptography algorithm based on cryptography message syntax by Ali, Mohammed Ahnaf

“…The problematic message uses light blue representation in simulation. …”
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A web-based implementation of k-means algorithms by Lee, Quan

“…The K-means algorithm has been around for over a century. …”
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Learning to filter text in forum message by Sainin, Mohd Shamrie

“…Applying the basic filtering technique in forum application has been discussed in [1].The paper explains about the use of the basic naïve Bayes algorithm to classify forum messages whether clean or bad where clean message has no bad words, while bad message contains one or more bad words. …”
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A new SMS spam detection method using both Content-Based and non Content-Based features by Sulaiman N.F., Jali M.Z.

Phishing attack detection using machine learning method by Jupin, John Arthur

“…There are several algorithms that can be used in the machine learning method to prevent the both attacks. …”
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Sentiment analysis using negative selection algorithm for Twitter’s messages / Nazirah Che Alhadi by Che Alhadi, Nazirah

“…This project is designed using negative selection algorithm to automatically classify the Twitter’s messages into its sentiment’s category based on important keyword recognition. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

“…This study aims to compare the performance of Boyer-Moore, Knuth morris pratt, and Horspool algorithms in searching for the meaning of words in the Java-Indonesian dictionary search application in terms of accuracy and processing time. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Cyberbullying detection: a machine learning approach by Yeong, Su Yen

“…In this project, a model was created to classify the text as cyberbullying message or non-cyberbullying message. This model combines a rule-based approach of sentiment analysis and a supervised machine learning algorithm to classify the text. …”
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Talkout : Protecting mental health application with a lightweight message encryption by Gavin Teo Juen

“…This project proposed a virtual mental health mobile application, called TalkOut, with a lightweight message encryption algorithm to protect patient's profile, conversation messages and treatment history. …”
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Intrusion detection on the in-vehicle network using machine learning by Sharmin, Shaila, Mansor, Hafizah

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Biometrics electronic purse by Abdul Rahman, Abdul Wahab, Eng, Chong Tan, S., M. Heng

“…This paper looked into using biometrics as a mean of authentication, thus requiring a new generation of Smart Card technology to be implemented in banking and multiple applications environment. …”
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Analysing machine learning models to detect disaster events using social media by Faris Azni Azlan, Mr.

An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…For example,the spammer changes patterns of message for making spam such as writing the message by JavaScript, using different advertising images and words to form features or attributes. …”
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Movie recommendation system / Najwa Syamimie Hasnu by Hasnu, Najwa Syamimie

“…PHPMyAdmin is used to store the dataset and also acts as a database for user information. The algorithm chosen was implemented using Java Programming language and was tested using Root Means Square Error (RMSE) formula.…”
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Risk Concentration for Context Assessment (RiCCA) of SMS Messages using Danger Theory by Kamahazira Binti Zainal

Spam classification based on supervised learning using grasshopper optimization algorithm and artificial neural network by Mumtazimah, Mohamad, Engku Fadzli Hasan, Syed Abdullah, Ghaleb, S.A.A., Ghanem, W.A.H.M.

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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…This project proposed a two color segmentation techniques such as K-means and Fuzzy C-means clustering algorithm that are accurately segment the desired images, which have the same color as the pre-selected pixels with background subtraction. …”
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