WhatToSee
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- A Fast Algorithm for Computing Hypergraph Transversals and its Application in Mining Emerging Patterns
- A Feature Selection Framework for Text Filtering Zhaohui Zheng Rohini Srihari Sargur Srihari CEDAR, Department of Computer Science and Engineering University at Buffalo, The State University of New York zzheng3,rohini,srihari @cedar.buffalo.edu
- A High-Performance Distributed Algorithm for Mining Association Rules Assaf Schuster, Ran Wolff, and Dan Trock Technion Israel Institute of Technology Email: assaf,ranw,dtrock @cs.technion.ac.il
- A Hybrid Data-Mining Approach in Genomics and Text Structures
- A K-NN Associated Fuzzy Evidential Reasoning Classifier with Adaptive Neighbor Selection Hongwei Zhu, Otman Basir Department of Systems Design Engineering, University of Waterloo 200 University Ave. W., Waterloo, Ontario, N2L 3G1, Canada h4zhu@engmail.uwaterloo.ca, obasir@uwaterloo.ca
- A User-driven and Quality-oriented Visualization for Mining Association Rules Julien Blanchard, Fabrice Guillet, Henri Briand IRIN Polytech'Nantes University of Nantes La Chantrerie BP50609 44306 Nantes cedex 3 France {julien.blanchard, fabrice.guillet, henri.briand}@polytech.univ-nantes.fr
- A new optimization criterion for generalized discriminant analysis on undersampled problems Jieping Ye Ravi Janardan Cheong Hee Park Haesun Park
- Active Sampling for Feature Selection Sriharsha Veeramachaneni Paolo Avesani ITC-IRST, Via Sommarive 18 - Loc.Pante,` I-38050 Povo, Trento, Italy E-mail: sriharsha,avesani @irst.itc.it
- An Algebra for Inductive Query Evaluation Sau Dan Lee Luc De Raedt Institut fur Informatik Albert-Ludwigs-Universitat Freiburg Georges-Kohler -Allee, Gebaude 079 D-79110 Freiburg im Breisgau Germany {danlee,deraedt}@informatik.uni-freiburg.de
- An Algorithm for the Exact Computation of the Centroid of Higher Dimensional Polyhedra and its Application to Kernel Machines Frederic Maire Smart Devices Laboratory, School of SEDC, IT Faculty, Queensland University of Technology, 2 George Street, GPO Box 2434, Brisbane Q 4001, Australia.
- Analyzing High-Dimensional Data by Subspace Validity Amihood Amir, Reuven Kashi, Nathan S. Netanyahu Bar-Ilan University Department of Computer Science 52900 Ramat-Gan, Israel amir,kashi,nathan @cs.biu.ac.il Daniel Keim, Markus Wawryniuk University of Konstanz Computer & Information Scienc 78457 Konstanz, Germany keim,wawryniu @informatik.uni-konstanz.de
- Applying Noise Handling Techniques to Genomic Data: A Case Study Choh Man Teng Institute for Human and Machine Cognition 40 South Alcaniz Street, Pensacola FL 32501, USA
- Association Rule Mining in Peer-to-Peer Systems Ran Wolff and Assaf Schuster Technion Israel Institute of Technology Email: ranw,assaf @cs.technion.ac.il
- Building Text Classifiers Using Positive and Unlabeled Examples Bing Liu Department of Computer Science University of Illinois at Chicago {liub@cs.uic.edu} Yang Dai Department of Bioengineering University of Illinois at Chicago {yangdai@uic.edu} Xiaoli Li, Wee Sun Lee School of Computing, National University of Singapore/Singapore-MIT Alliance {lixl, leews}@comp.nus.edu.sg Philip S. Yu IBM T. J. Watson Research Center, Yorktown Heights, NY 10598, USA
- CBC: Clustering Based Text Classification Requiring Minimal Labeled Data Hua-Jun Zeng1 Xuan-Hui Wang2 Zheng Chen1 Hongjun Lu3 Wei-Ying Ma1
- Center-Based Indexing for Nearest Neighbors Search Arkadiusz Wojna Institute of Informatics, Warsaw University ul. Banacha 2, 02-097 Warsaw, Poland wojna@mimuw.edu.pl
- Chang-Tien Lu Dept. of Computer Science Virginia Polytechnic Institute and State University 7054 Haycock Road Falls Church, VA 22043 ctlu@vt.edu
- Change Profiles Taneli Mielikainen HIIT Basic Research Unit Department of Computer Science University of Helsinki, Finland Taneli.Mielikainen@cs.Helsinki.fi
- Class Decomposition via Clustering: A New Framework for Low-Variance Classifiers Ricardo Vilalta, Murali-Krishna Achari, and Christoph F. Eick Department of Computer Science University of Houston Houston TX, 77204-3010, USA {vilalta, amkchari, ceick}@cs.uh.edu
- Clustering Item Data Sets with Association-Taxonomy Similarity Ching-Huang Yun*, Kun-Ta Chuang+ and Ming-Syan Chen*+ Department of Electrical Engineering* Graduate Institute of Communication Engineering+ National Taiwan University Taipei, Taiwan, ROC E-mail: chyun@arbor.ee.ntu.edu.tw, doug@arbor.ee.ntu.edu.tw, mschen@cc.ee.ntu.edu.tw
- Combining Multiple Weak Clusterings Alexander Topchy, Anil K. Jain, and William Punch Computer Science Department, Michigan State University, East Lansing, MI, 48824, USA {topchyal, jain, punch}@cse.msu.edu
- Combining the web content and usage mining to understand the visitor behavior in a web site Juan Velasquez, Hiroshi Yasuda and Terumasa Aoki “ Research Center for Advanced Science and Technology, University of Tokyo, Japan E-mail:{jvelasqu,yasuda,aoki}@mpeg.rcast.u-tokyo.ac.jp
- Comparing Naive Bayes, Decision Trees, and SVM with AUC and Accuracy Jin Huang Jingjing Lu Charles X. Ling Department of Computer Science The University of Western Ontario London, Ontario, Canada N6A 5B7 fg@csd.uwo.ca jhuang, jlu, cling
- Comparing Pure Parallel Ensemble Creation Techniques Against Bagging Lawrence O. Hall, Kevin W. Bowyer1, Robert E. Banfield, Divya Bhadoria W. Philip Kegelmeyer2 and Steven Eschrich Computer Science & Engineering, University of South Florida, Tampa, Florida 33620-5399 {hall, rbanfiel, dbhadori}@csee.usf.edu
- Complex Spatial Relationships Robert Munro and Sanjay Chawla and Pei Sun School of Information Technologies University of Sydney rmunro, chawla, psun2712 @it.usyd.edu.au
- Cost-Sensitive Learning by Cost-Proportionate Example Weighting Bianca Zadrozny, John Langford , Naoki Abe Mathematical Sciences Department IBM T. J. Watson Research Center Yorktown Heights, NY 10598
- Detecting Interesting Exceptions from Medical Test Data with Visual Summarization Einoshin Suzuki1 Takeshi Watanabe1 Division of Electrical and Computer Engineering, Yokohama National University, Japan suzuki@ynu.ac.jp, nabekun@slab.dnj.ynu.ac.jp Hideto Yokoi2 Katsuhiko Takabayashi2 2. Chiba University Hospital, Japan yokoih@telemed.ho.chiba-u.ac.jp, takaba@ho.chiba-u.ac.jp
- Dimensionality Reduction Using Kernel Pooled Local Discriminant Information
- Direct Interesting Rule Generation
- Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift Jeremy Z. Kolter and Marcus A. Maloof Department of Computer Science Georgetown University Washington, DC 20057-1232, USA {jzk, maloof}@cs.georgetown.edu
- Effectiveness of Information Extraction, Multi-Relational, and Semi-Supervised Learning for Predicting Functional Properties of Genes
- Efficient Data Mining for Maximal Frequent Subtrees
- Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism Jun Huan, Wei Wang, Jan Prins Department of Computer Science University of North Carolina, Chapel Hill {huan, weiwang, prins}@cs.unc.edu
- Efficient Multidimensional Quantitative Hypotheses Generation Amihood Amir Department of Computer Science Bar-Ilan University,52900 Ramat-Gan, Israel (972-3)531-8770, amir@cs.biu.ac.il and College of Computing, Georgia Tech, Atlanta, GA 30332-0280 Reuven Kashi RUTCOR-Rutgers Center for Operations Research Rutgers, The State University of New Jersey 640 Bartholomew Rd, Piscataway, NJ 08854-8003 kashi@cs.biu.ac.il Nathan S. Netanyahu Department of Computer Science Bar-Ilan University 52900 Ramat-Gan, Israel (972-3)531-8865, nathan@cs.biu.ac.il and Center for Automation Research, Univ. of Maryland, College Park, MD 20742
- Efficient Nonlinear Dimension Reduction for Clustered Data Using Kernel Functions Cheong Hee Park Haesun Park Dept. of Computer Science and Engineering University of Minnesota Minneapolis, MN 55455 chpark@cs.umn.edu hpark@cs.umn.edu
- Efficient Subsequence Matching in Time Series Databases Under Time and Amplitude Transformations
- Enhancing Techniques for Efficient Topic Hierarchy Integration
- Ensembles of Cascading Trees Jinyan Li Huiqing Liu Institute for Infocomm Research 21 Heng Mui Keng Terrace, Singapore 119613 jinyan,huiqing @i2r.a-star.edu.sg
- Eren Manavoglu Pennsylvania State University 001 Thomas Building University Park, PA 16802 manavogl@cse.psu.edu
- ExAMiner: Optimized Level-wise Frequent Pattern Mining with Monotone Constraints Francesco Bonchi, Fosca Giannotti Pisa KDD Laboratory
- Exploiting Unlabeled Data for Improving Accuracy of Predictive Data Mining Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Zoran Obradovic Center for Information Science and Technology, Temple University, Philadelphia, PA 19122, USA {kangpeng, vucetic, hanbo, hongbox, zoran}@ist.temple.edu
- Facilitating Fuzzy Association Rules Mining by Using Multi-Objective Genetic Algorithms for Automated Clustering
- Fast PNN-based Clustering Using K-nearest Neighbor Graph Pasi Fränti, Olli Virmajoki and Ville Hautamäki Department of Computer Science, University of Joensuu, PB 111, FIN-80101 Joensuu, Finland. franti@cs.joensuu.fi, ovirma@cs.joensuu.fi, villeh@cs.joensuu.fi
- Findings from a Practical Project Concerning Web Usage Mining
- Frequent Sub-Structure-Based Approaches for Classifying Chemical Compounds Mukund Deshpande, Michihiro Kuramochi and George Karypis University of Minnesota, Department of Computer Science/Army HPC Research Center Minneapolis, MN 55455
- Frequent-Pattern based Iterative Projected Clustering Man Lung Yiu and Nikos Mamoulis Department of Computer Science and Information Systems University of Hong Kong Pokfulam Road, Hong Kong mlyiu2,nikos @csis.hku.hk
- General MC: Estimating Boundary of Positive Class from Small Positive Data Hwanjo Yu hwanjoyu@cs.uiuc.edu Department of Computer Science University of Illinois at Urbana-Champaign Urbana, IL 61801 USA
- Icon-based Visualization of Large High-Dimensional Datasets Ping Chen Chenyi Hu Wei Ding Heloise Lynn, Yves Simon
- Identifying Markov Blankets with Decision Tree Induction
- Impact Studies and Sensitivity Analysis in Medical Data Mining with ROC-based Genetic Learning Michele` Sebag Jer“ ome^ Aze“ Noel Lucas PCRI, CNRS UMR 86-23, Universite“ Paris-Sud Orsay, 91405 France Michele.Sebag, Jerome.Aze, Noel.Lucas @lri.fr
- Improving Home Automation by Discovering Regularly Occurring Device Usage Patterns Edwin O. Heierman, III Diane J. Cook
- Indexing and Mining Free Trees Yun Chi, Yirong Yang, Richard R. Muntz Department of Computer Science University of California, Los Angeles, CA 90095 {ychi,yyr,muntz}@cs.ucla.edu
- Inference of Protein-Protein Interactions by Unlikely Profile Pair Byung-Hoon Park, George Ostrouchov, Gong-Xin Yu, Al Geist, Andrey Gorin, and Nagiza F. Samatova Computational Biology Group, Computer Science and Mathematics Division, Oak Ridge National Laboratory {parkbh, samatovan}@ornl.gov
- Information Theoretic Clustering of Sparse Co-Occurrence Data Inderjit S. Dhillon and Yuqiang Guan Department of Computer Sciences University of Texas Austin, TX 78712-1188, USA inderjit, yguan@cs.utexas.edu
- Integrating Fuzziness into OLAP for Multidimensional Fuzzy Association Rules Mining
- Interactive Visualization and Navigation in Large Data Collections using the Hyperbolic Space Jorg Walter · Jorg Ontrup · Daniel Wessling · Helge Ritter Neuroinformatics Group · Department of Computer Science University of Bielefeld · D-33615 Bielefeld · Germany E-mail: walter@techfak.uni-bielefeld.de
- Interpretations of Association Rules by Granular Computing
- Introducing Uncertainty into Pattern Discovery in Temporal Event Sequences Xingzhi Sun, Maria E. Orlowska, and Xue Li School of Information Technology and Electrical Engineering The University of Queensland, Australia {sun, maria, xueli}@itee.uq.edu.au
- Is random model better? On its accuracy and efficiency Wei Fan, Haixun Wang, Philip S. Yu, and Sheng Ma
- K-D Decision Tree:
- Learning Bayesian Networks from Incomplete Data Based on EMI Method
- Learning Rules for Anomaly Detection of Hostile Network Traffic Matthew V. Mahoney and Philip K. Chan Department of Computer Sciences Florida Institute of Technology Melbourne, FL 32901 {mmahoney,pkc}@cs.fit.edu
- Links Between Kleinberg's Hubs and Authorities, Correspondence Analysis, and Markov Chains
- Localized Prediction of Continuous Target Variables Using Hierarchical Clustering Aleksandar Lazarevic1, Ramdev Kanapady2, Chandrika Kamath3, Vipin Kumar1, Kumar Tamma2
- MPIS: Maximal-Profit Item Selection with Cross-Selling Considerations
- MaPle: A Fast Algorithm for Maximal Pattern-based Clustering Jian Pei Xiaoling Zhang Moonjung Cho Haixun Wang Philip S. Yu
- Mining Frequent Itemsets in Distributed and Dynamic Databases M. E. Otey C. Wang S. Parthasarathy A. Veloso W. Meira Jr.
- Mining Plans for Customer-Class Transformation
- Mining Production Data with Neural Network & CART Mingkun Li1, Shuo Feng1, Ishwar K. Sethi1, Jason Luciow2, Keith Wagner2
- Mining Relevant Text from Unlabelled Documents Daniel Barbara“ Carlotta Domeniconi Ning Kang Information and Software Engineering Department George Mason University Fairfax, VA 22030 dbarbara,cdomenic,nkang @gmu.edu
- Mining Semantic Networks for Knowledge Discovery
- Mining Significant Pairs of Patterns from Graph Structures with Class Labels Akihiro Inokuchi and Hisashi Kashima Tokyo Research Laboratory, IBM Japan 1623-14, Shimotsuruma, Yamato, Kanagawa, 242-8502, Japan inokuchi,hkashima @jp.ibm.com
- Mining Strong Affinity Association Patterns in Data Sets with Skewed Support Distribution
- Mining the Web to Discover the Meanings of an Ambiguous Word
- Model Stability: A key factor in determining whether an algorithm produces an optimal model from a matching distribution Kai Ming Ting and Regina Jing Ying Quek KaiMing.Ting@infotech.monash.edu.au Gippsland School of Computing and Information Technology Monash University, Victoria 3842, Australia.
- OP-Cluster: Clustering by Tendency in High Dimensional Space Jinze Liu and Wei Wang Computer Science Department University of North Carolina Chapel Hill, NC, 27599 {liuj, weiwang }@cs.unc.edu
- On Precision and Recall of Multi-Attribute Data Extraction from Semistructured Sources
- Ontologies Improve Text Document Clustering Andreas Hotho, Steffen Staab, Gerd Stumme {hotho,staab,stumme}@aifb.uni-karlsruhe.de Institute AIFB, University of Karlsruhe, 76128 Karlsruhe, Germany
- Optimized Disjunctive Association Rules via Sampling
- Parsing Without a Grammar: Making Sense of Unknown File Formats Levon Lloyd and Steven Skiena Department of Computer Science State University of New York at Stony Brook Stony Brook, NY 11794-4400 {lloyd, skiena}@cs.sunysb.edu
- Pattern Discovery based on Rule Induction and Taxonomy Generation Shusaku Tsumoto and Shoji Hirano Department of Medical Informatics, Shimane University, School of Medicine, Enya-cho Izumo City, Shimane 693-8501 Japan tsumoto@computer.org, hirano@ieee.org
- PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets Daniel A. Keim, Christian Panse, Mike Sips University of Konstanz, Germany
- Postprocessing Decision Trees to Extract Actionable Knowledge
- Privacy-Preserving Collaborative Filtering Using Randomized Perturbation Techniques Huseyin Polat and Wenliang Du Systems Assurance Institute Department of Electrical Engineering and Computer Science Syracuse University, 121 Link Hall, Syracuse, NY 13244 E-mail: hpolat,wedu @ecs.syr.edu
- Privacy-preserving Distributed Clustering using Generative Models Srujana Merugu and Joydeep Ghosh Electrical and Computer Engineering University of Texas at Austin Austin, TX 78712 merugu, ghosh @ece.utexas.edu
- Protecting Sensitive Knowledge By Data Sanitization
- Regression Clustering Bin Zhang Hewlett-Packard Research Laboratories, Palo Alto, CA 94304 bzhang@hpl.hp.com
- Regulatory Element Discovery Using Tree-structured Models Tu Minh Phuong, Doheon Lee, Kwang Hyung Lee Department of BioSystems, Korea Advanced Institute of Science and Technology 373-1 Guseong-dong Yuseong-gu Daejeon 305-701, Korea {phuong, dhlee, khlee}@bioif.kaist.ac.kr
- SVM Based Models for Predicting Foreign Currency Exchange Rates
- Scalable Model-based Clustering by Working on Data Summaries
- Segmenting Customer Transactions Using a Pattern-Based Clustering Approach Yinghui Yang and Balaji Padmanabhan Operations and Information Management Department The Wharton School, University of Pennsylvania {yiyang, balaji}@wharton.upenn.edu
- Semantic Role Parsing: Adding Semantic Structure to Unstructured Text Sameer Pradhan, Kadri Hacioglu, Wayne Ward, James H. Martin, Daniel Jurafsky Center for Spoken Language Research, University of Colorado, Boulder, CO 80303
- Sentiment Analyzer: Extracting Sentiments about a Given Topic using Natural Language Processing Techniques
- Sequence Modeling with Mixtures of Conditional Maximum Entropy Distributions
- Simple Estimators for Relational Bayesian Classifiers Jennifer Neville, David Jensen and Brian Gallagher Knowledge Discovery Laboratory, Department of Computer Science, University of Massachusetts Amherst, 140 Governors Drive, Amherst, MA 01003 USA {jneville | jensen | bgallag}@cs.umass.edu
- Spatial Interest Pixels (SIPs): Useful Low-Level Features of Visual Media Data
- Statistical Relational Learning for Document Mining
- Structure Search and Stability Enhancement of Bayesian Networks Hanchuan Peng and Chris Ding Computational Research Division, Lawrence Berkeley National Laboratory, University of California, Berkeley, CA, 94720, USA Email: hpeng@lbl.gov, chqding@lbl.gov
- T-Trees, Vertical Partitioning and Distributed Association Rule Mining Frans Coenen, Paul Leng and Shakil Ahmed Department of Computer Science, The University of Liverpool Liverpool, L69 3BX, UK frans,phl,shakil @csc.liv.ac.uk
- TECNO-STREAMS: Tracking Evolving Clusters in Noisy Data Streams with a Scalable Immune System Learning Model Olfa Nasraoui, Cesar Cardona Uribe, Carlos Rojas Coronel Department of Electrical and Computer Engineering The University of Memphis 206 Engineering Science Bldg., Memphis, TN 38152 onasraou,ccardona,crojas @memphis.edu Fabio Gonzalez Department of Systems and Industrial Engineering National University of Colombia Bogota, Colombia email: fgonza@ing.unal.edu.co
- TSP: Mining Top-K Closed Sequential Patterns Petre Tzvetkov Xifeng Yan Jiawei Han Department of Computer Science University of Illinois at Urbana-Champaign, Illinois, U.S.A. tzvetkov, xyan, hanj @cs.uiuc.edu
- Text Mining for a Clear Picture of Defect Reports: A Praxis Report
- The Rough Set Approach to Association Rule Mining
- Towards Simple, Easy-to-Understand, yet Accurate Classifiers
- Tree-structured Partitioning Based on Splitting Histograms of Distances
- Understanding Helicoverpa armigera Pest Population Dynamics related to Chickpea Crop Using Neural Networks
- Unsupervised Link Discovery in Multi-relational Data via Rarity Analysis
- Using Discriminant Analysis for Multi-class Classification Tao Li Shenghuo Zhu Mitsunori OgiharaŽ
- Visualization of Rule's Similarity using Multidimensional Scaling Shusaku Tsumoto and Shoji Hirano Department of Medical Informatics, Shimane University, School of Medicine, Enya-cho Izumo City, Shimane 693-8501 Japan tsumoto@computer.org, hirano@ieee.org
- Zigzag: a new algorithm for mining large inclusion dependencies in databases Fabien De Marchi, Jean-Marc Petit Laboratoire LIMOS, UMR CNRS 6158 Universite“ Blaise Pascal - Clermont-Ferrand II, 24 avenue des Landais 63 177 Aubiere` cedex, France {demarchi,jmpetit}@math.univ-bpclermont.fr