نتایج جستجو برای: kdd cup 99

تعداد نتایج: 84698  

2012
Todd G. McKenzie Chun-Sung Ferng Yao-Nan Chen Chun-Liang Li Cheng-Hao Tsai Kuan-Wei Wu Ya-Hsuan Chang Chung-Yi Li Wei-Shih Lin Shu-Hao Yu Chieh-Yen Lin Po-Wei Wang Chia-Mau Ni Wei-Lun Su Tsung-Ting Kuo Chen-Tse Tsai Po-Lung Chen Rong-Bing Chiu Ku-Chun Chou Yu-Cheng Chou Chien-Chih Wang Chen-Hung Wu Hsuan-Tien Lin Chih-Jen Lin Shou-De Lin

The track 2 problem in KDD Cup 2011 (music recommendation) is to discriminate between music tracks highly rated by a given user from those which are overall highly rated, but not rated by the given user. The training dataset consists of not only user rating history but also the taxonomic information of track, artist, album, and genre. This paper describes the solution of the National Taiwan Uni...

Journal: :Journal of Machine Learning Research 2012
Tianqi Chen Weinan Zhang Qiuxia Lu Kailong Chen Zhao Zheng Yong Yu

In this paper we introduce SVDFeature, a machine learning toolkit for feature-based collaborative filtering. SVDFeature is designed to efficiently solve the feature-based matrix factorization. The feature-based setting allows us to build factorization models incorporating side information such as temporal dynamics, neighborhood relationship, and hierarchical information. The toolkit is capable ...

2009
Patrick Doetsch Christian Buck Pavlo Golik Niklas Hoppe Michael Kramp Johannes Laudenberg Christian Oberdörfer Pascal Steingrube Jens Forster Arne Mauser

In this work, we describe our approach to the “Small Challenge” of the KDD cup 2009, the prediction of three aspects of customer behavior for a telecommunications service provider. Our most successful method was a Logistic Model Tree with AUC as split criterion using predictions from boosted decision stumps as features. This was the best submission for the “Small Challenge” that did not use add...

2012
R. Sudha

With popularization of internet, internet attack cases are increasing, and attack methods differs each day, thus information safety problem has became a significant issue all over the world. Nowadays, it is an urgent need to detect, identify and hold up such attacks effectively. Intrusion detection is the act of detecting actions that attempt to compromise the confidentiality, integrity or avai...

2011
R. Shanmugavadivu

IDS which are increasingly a key part of system defense are used to identify abnormal activities in a computer system. In general, the traditional intrusion detection relies on the extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been used in ...

2015
N. Priya

To make an immune-inspired network intrusion detection system (IDS) effective, this paper proposes a new framework, which includes our avidity-model based clonal selection (AMCS) algorithm as core element. The AMCS algorithm uses an improved representation for antigens (corresponding to network access patterns) and detectors (corresponding to detection rules). In particular, a bio-inspired tech...

2012
K.KEERTHI P.SREENIVAS

IDS (Intrusion Detection system) is an active and driving defense technology. This project mainly focuses on intrusion detection based on data mining. Data mining is to identify valid, novel, potentially useful, and ultimately understandable patterns in massive data. This project presents an approach to detect intrusion based on data mining frame work. Intrusion Detection System (IDS) is a popu...

2013
Karthik G

Data safekeeping and security has been a key concern in the rapidly growing computer systems and networks. One of the recent methods for identifying any abnormal activities staging in a computer system is carried out by Intrusion Detection Systems (IDS) and it forms a significant portion of system defence against attacks. Various methods based on Intrusion Detection Systems have been proposed i...

2015
Safaa O. Al-mamory Firas S. Jassim

Despite the rapid progress of the information technology, protecting computers and networks remain a major problem for most authors. In this paper, two grains levels intrusion detection system (IDS) is suggested (fine-grained and coarse-grained). In normal case, where intrusions are not detected, the most suitable IDS level is the coarse-grained to increase IDS performance. As soon as any intru...

2014
Dheeraj Basant Shukla Gajendra Singh Chandel

Classification of network traffic is extensively required mainly for many network management tasks such as flow prioritization, traffic shaping/policing, and diagnostic monitoring. Many approaches have been evolved for this purpose. The classical approach such as port number or payload analysis methods has their own limitations. For example, some applications uses dynamic port number and encryp...

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