Search Results - (( variable detection mining algorithm ) OR ( java applications mining algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Potential norms detection in social agent societies by Mahmoud M.A., Mustapha A., Ahmad M.S., Ahmad A., Yusoff M.Z.M., Hamid N.H.A.

“…In this paper, we propose a norms mining algorithm that detects a domain's potential norms, which we called the Potential Norms Mining Algorithm (PNMA). …”

Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

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Building norms-adaptable agents from Potential Norms Detection Technique (PNDT) by Mahmoud M.A., Ahmad M.S., Ahmad A., Mustapha A., Yusoff M.Z.M., Hamid N.H.A.

“…This technique enables an agent to update its norms even in the absence of sanctions from a third-party enforcement authority as found in some work, which entail sanctions by a third-party to detect and identify the norms. The PNDT consists of five components: agent's belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent's belief base with new normative protocol. …”

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Cancer Prediction Based On Data Mining Using Decision Tree Algorithm by Loh, Kin Ming

“…Many studies have been conducted in order to predict cancer. Different data mining method has showed up with its related algorithms were adopted by different research. …”
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Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Building norms-adaptable agents from Potential Norms Detection Technique (PNDT) by Mahmoud, Moamin Ahmed, Ahmad, Mohd Sharifuddin, Ahmad, Azhana, Mustapha, Aida, Mohd Yusoff, Mohd Zaliman, Abdul Hamid, Nurzeatul Hamimah

“…This technique enables an agent to update its norms even in the absence of sanctions from a third-party enforcement authority as found in some work, which entail sanctions by a third-party to detect and identify the norms. The PNDT consists of five components: agent’s belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent’s belief base with new normative protocol. …”
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Development and implementation of a technique for norms-adaptable agents in open multi-agent communities by Mahmoud M., Ahmad M.S., Mohd Yusoff M.Z.

Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Sentiment-analysis to detect early depressive symptom in Bangla language from social media: a review study by Hassan, Md. Hasibul, Kamaruddin, Azrina, Azmi Murad, Masrah Azrifah

“…The review shows that the mostly used method in Sentiment-analysis is Machine Learning in the field of Opinion-mining. Furthermore, we have identified another variable that can be included to improve the existing algorithm.…”
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An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach by Mohamed Yassin, Warusia

“…Detection methods based on statistical and data mining techniques are widely deployed as anomaly-based detection system (ADS). …”
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A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping by Althuwaynee, Omar F., Pradhan, Biswajeet, Park, Hyuck Jin, Lee, Jung Hyun

“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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Toward Predicting Student�s Academic Performance Using Artificial Neural Networks (ANNs) by Baashar Y., Alkawsi G., Mustafa A., Alkahtani A.A., Alsariera Y.A., Ali A.Q., Hashim W., Tiong S.K.

“…No pattern was detected regarding selecting the input variables as they are mainly based on the context of the study and the availability of data. …”

Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…Infected palms are asymptomatic throughout the disease's early stages, making disease detection challenging. The survival of affected trees must detect BSR at the mild infected (T1) stage. …”
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Identification of debris flow initiation zones using topographic model and airborne laser scanning data by Lay, Usman Salihu, Pradhan, Biswajeet

“…MARSpline multivariate data mining predictive approach was implemented using morphometric indices and topographical derived parameter as independent variables. …”
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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

“…In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. With large variability in SOM, the field presents a special situation and thus, the result could be specific to the study site. …”
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