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3rd IEEE International conference on cloud computing and Intelligence Systems (ccIS)

作者： Han, Xu Lv, Tao Wei, Lin Wu, Yanyan Liu, Jianyi Wang, cong Beijing Univ Posts & Telecommun Beijing 100876 Peoples R China Beijing Govt Comp Emergency Response Ctr Beijing Peoples R China

ISBN: (纸本)9781479947195

To found security events from web logs has become an important aspect of network security. This paper proposes a website anomaly detection model based on security-log-analysis. After creating a anomaly feature sets of the model, c4.5 algorithm was used to improve feature sets, making the abnormal records in feature sets store hierarchically. compared logs in website with the treated feature stes, the model ultimately achieves the purpose of checking website's security event fast and accurately.

关键词： Log analysis Anomaly detection c4.5 algorithm Feature sets

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Disease Forecasting System Using Data Mining Methods

Disease Forecasting System Using Data Mining Methods

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International conference on Intelligent computing Applications (IcIcA)

作者： Banu, M. A. Nishara Gomathy, B. Bannari Amman Inst Technol Dept Comp Sci & Engn Sathyamangalam India

ISBN: (纸本)9781479939664

The healthcare industry collects large amounts of healthcare information which cannot be mined to find unknown information for efficient evaluation. Discovery of buried patterns frequently goes unexploited. Heart disease is a term for defining a huge amount of healthcare conditions that are related to the heart. This medicinal condition defines the unpredicted health conditions that directly control all the parts of the heart. Different data mining techniques such as association rule mining, classification, clustering are used to predict the heart disease in health care industry. The heart disease database is preprocessed to make the mining process more efficient. The preprocessed data is clustered using clustering algorithms like K-means to cluster relevant data in database. Maximal Frequent Itemset algorithm (MAFIA) is used for mining maximal frequent patterns in heart disease database. The frequent patterns can be classified using c4.5 algorithm as training algorithm using the concept of information entropy. The results showed that the designed prediction system is capable of predicting the heart attack successfully.

关键词： Data mining K-means clustering MAFIA (Maximal Frequent Itemset algorithm c4.5 algorithm

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A Hybrid System for Reducing Memory and Time Overhead of Intrusion Detection System

A Hybrid System for Reducing Memory and Time Overhead of Int...

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2nd IFIP Tc5/8 International conference on IcT-EurAsia

作者： chen, Zhi-Guo Kim, Sung-Ryul Konkuk Univ Div Internet & Multimedia Engn Seoul South Korea

ISBN: (纸本)9783642550324;9783642550317

With the growing use of the internet worldwide, internet security becomes more and more important. There are many techniques available for intrusion detection. However, there remain various issues to be improved, such as detection rate, false positive rate, memory overhead, time overhead, and so on. In this paper, a new hybrid system for network intrusion detection system using principal component analysis and c4.5 is presented, which has a good detection rate and keeps false positive and false negative rate at an acceptable level for different types of network attacks. Especially, this system can effectively reduce the memory overhead and the time overhead of building the intrusion detection model. These claims are verified by experimental results on the KDD cup 99 benchmark network intrusion detection dataset.

关键词： Intrusion Detection System Principal component Analysis algorithm c4.5 algorithm Time Overhead and Memory Overhead

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A Smart Bus Tracking System Based on Location-Aware Services and QR codes

A Smart Bus Tracking System Based on Location-Aware Services...

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IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA)

作者： Eken, Suleyman Sayar, Ahmet Kocaeli Univ Dept Comp Engn Kocaeli Turkey

ISBN: (纸本)9781479930203

When it comes to taking the public transportation, time and patience are of essence. In other words, many people using public transport buses have experienced time loss because of waiting at the bus stops. In this paper, we proposed smart bus tracking system that any passenger with a smart phone or mobile device with the QR (Quick Response) code reader can scan QR codes placed at bus stops to view estimated bus arrival times, buses' current locations, and bus routes on a map. Anyone can access these maps and have the option to sign up to receive free alerts about expected bus arrival times for the interested buses and related routes via SMS and e-mails. We used c4.5 (a statistical classifier) algorithm for the estimation of bus arrival times to minimize the passengers waiting time. GPS (Global Positioning System) and Google Maps are used for navigation and display services, respectively.

关键词： QR codes GPS Smart bus stops c4.5 algorithm Smart phones Interactive maps

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comparison of classification Techniques for predicting the cognitive Skill of Students in Education Environment 5

Comparison of Classification Techniques for predicting the C...

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5th IEEE International conference on computational Intelligence and computing Research (IEEE IccIc)

作者： Mayilvaganan, M. Kalpanadevi, D. PSG Coll Arts & Sci Coll Dept Comp Sci Coimbatore Tamil Nadu India

ISBN: (纸本)9781479939756

The proposed methodology involves to compares classification techniques for predicting the cognitive skill of students which can be evaluate by conducting the online test. The paper focuses the comparative performance of c4.5 algorithm, Naive Bayes classifier algorithm which one is well suited accuracy for predicting the skill of expertise by experimenting in Rapid miner.

关键词： Datamining c4.5 algorithm Naive Bayes classification Rapid Miner

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Sumoylation may play an important role in modification of large number of proteins associated with heat stress in plants

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Proceedings of the National Academy of Sciences India Section B - Biological Sciences 2014年第3期84卷 709-712页

作者： Singh, Avantika Vats, Garima chandra, Nidhi Grover, Monendra National Bureau of Plant Genetic Resources Pusa Campus New Delhi India Amity University Noida Uttar Pradesh India Center for Agricultural Bioinformatics Indian Agricultural Statistics Research Institute New Delhi 110012 Library Avenue Pusa Road India

Heat stress is an important factor affecting the agricultural production. At the molecular level post translational modifications have been shown to be influenced in plants under heat stress. The authors have studied palmitoylation, sumoylation, S-nitrosylation and nitration in the plant gene sequences associated or not associated with heat stress. In the present paper it has been shown that sumoylation is an important property which is possibly influences a large number of proteins associated with heat stress in a wide variety of plants. This property can be utilized for identifying novel sequences associated with heat stress in plants. © 2013 The National Academy of Sciences, India.

关键词： c4.5 algorithm Heat stress Post translational modification Weka

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Association Rule Sharing Model for Privacy Preservation and collaborative Data Mining Efficiency

Association Rule Sharing Model for Privacy Preservation and ...

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conference on Recent Advances in Engineering and computational Sciences (RAEcS)

作者： KumaraSwamy, S. Manjula, S. H. Venugopal, K. R. Iyengar, S. S. Patnaik, L. M. Bangalore Univ Univ Visvesvaraya Coll Engn Dept Comp Sci & Engn Bangalore 560001 Karnataka India Florida Int Univ Miami FL 33199 USA Indian Inst Sci Bangalore 560012 Karnataka India

ISBN: (纸本)9781479922918

The disclosure of information and its misuse in Privacy Preserving Data Mining (PPDM) systems is a concern to the parties involved. In PPDM systems data is available amongst multiple parties collaborating to achieve cumulative mining accuracy. The vertically partitioned data available with the parties involved cannot provide accurate mining results when compared to the collaborative mining results. To overcome the privacy issue in data disclosure this paper describes a Key Distribution-Less Privacy Preserving Data Mining (KDLPPDM) system in which the publication of local association rules generated by the parties is published. The association rules are securely combined to form the combined rule set using the commutative RSA algorithm. The combined rule sets established are used to classify or mine the data. The results discussed in this paper compare the accuracy of the rules generated using the c4. 5 based KDLPPDM system and the cS. 0 based KDLPPDM system using receiver operating characteristics curves (ROc).

关键词： Privacy Preserving Data Mining Vertically Partitioned Data Association Rules c4.5 algorithm See5.0/c5.0 algorithm commutative RSA ROc

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Association Analysis and Prediction for IPTV Service Data and User's QoE

Association Analysis and Prediction for IPTV Service Data an...

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International conference on Wireless communications and Signal Processing

作者： Siying Sun Xin Wei Lei Wang Jianxin chen College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467376884

In order to provide good service and improve user's feeling and degree of satisfaction, video service providers are now interested in understanding the influence of attributes on Quality of Experience (QoE). In this paper, based on IPTV business, we study the relationship between alarming data from IPTV set-top boxes and the user's QoE. First, data cleaning and analysis are performed. After these procedures, the important attributes influencing QoE are selected. Then decision tree is used for modeling dataset. Here information entropy minimization heuristic is adopted to discretize continuous-valued attributes and the improved c4.5 algorithm is designed to fastly and accurately build the tree. Experimental results show that the proposed scheme can indeed improve the prediction accuracy when compared with other competing schemes.

关键词： QoE Decision tree Discretization c4.5 algorithm

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The Improvement of c4.5 algorithm and case Study

The Improvement of C4.5 Algorithm and Case Study

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2nd International Symposium on computational Intelligence and Design

作者： Li Rui Wei Xian-mei Yu Xue-wei Dalian Jiaotong Univ Software Inst Dalian Peoples R China

ISBN: (纸本)9780769538655

The paper introduces a balanced coefficient to improve the veracity of c4.5 algorithm. It can be fixed by decision maker according to priori intellectual and domain intellectual. It harmonized the information gain-ratio of each attributes artificially in specific environment. The classification is more veracious and rational by the decision tree made from the improved algorithm. And compared the improved algorithm to c4.5 algorithm by analyzing examples, to prove the efficiency of the improved algorithm.

关键词： classification of data Decision tree c4.5 algorithm Degree of balance coefficient

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A MODEL FOR WEBSITE ANOMALY DETEcTION BASED ON LOG ANALYSIS

A MODEL FOR WEBSITE ANOMALY DETECTION BASED ON LOG ANALYSIS

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2014 IEEE 3rd International conference on cloud computing and Intelligence Systems

作者： Xu Han Tao Lv Lin Wei Yanyan Wu Jianyi Liu cong Wang Beijing University of Posts and Telecommunications

To found security events from web logs has become an important aspect of network *** paper proposes a website anomaly detection model based on *** creating a anomaly feature sets of the model,c4.5 algorithm was used to improve feature sets,making the abnormal records in feature sets store *** logs in website with the treated feature stes,the model ultimately achieves the purpose of checking website’s security event fast and accurately.

关键词： Log analysis Anomaly detection c4.5 algorithm Feature sets

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