- Targeting the Right Students Using Data Mining The education domain offers a fertile ground for many interesting
- Visual Analysis of the Behavior of Discovered Rules Kaidi Zhao, Bing Liu
- Negative Training Data can be Harmful to Text Classification Xiao-Li Li Bing Liu See-Kiong Ng
- Distributional Similarity vs. PU Learning for Entity Set Expansion Institute for Infocomm Research,
- OPINION MINING Department of Computer Science
- Mining Comparative Sentences and Relations Nitin Jindal and Bing Liu
- NET -A System for Extracting Web Data from Flat and Nested Data Records
- Web Data Extraction Based on Partial Tree Alignment Yanhong Zhai
- Mining and Summarizing Customer Reviews Minqing Hu and Bing Liu
- Mining Opinion Features in Customer Reviews Minqing Hu and Bing Liu
- Building Text Classifiers Using Positive and Unlabeled Examples Department of Computer Science
- Experimental Studies of the Universal Chemical Key (UCK) Algorithm on the NCI Database of Chemical Compounds
- Learning with Positive and Unlabeled Examples Using Weighted Logistic Regression
- Querying Multiple Sets of Discovered Rules Rule mining is an important data mining task that has been
- Visualizing Web Site Comparisons Bing Liu, Kaidi Zhao and Lan Yi
- Exploration Mining in Diabetic Patients Databases: Findings and Conclusions
- Using General Impressions to Analyze Discovered Classification Rules Bing Liu, Wynne Hsu and Shu Chen
- Current machine learning and discovery tech niques focus on discovering rules or regularities
- Scoring the Data Using Association Rules In many data mining applications, the objective is to select data cases of a target class.
- Discovering Unexpected Information from Your Competitors' Web Sites
- Visually Aided Exploration of Interesting Association Rules
- Integrating Classification and Association Rule Mining Bing Liu Wynne Hsu Yiming Ma
- Learning to Identify Unexpected Instances in the Test Set Institute for Infocomm
- Eliminating Noisy Information in Web Pages for Data Mining
- Analyzing the Interestingness of Association Rules from the Temporal Dimension Bing Liu, Yiming Ma
- Using Knowledge to Isolate Search in Route Finding Department of Information Systems and Computer Science
- MultiLevel Organization and Summarization of the Discovered Rules
- Learning from Positive and Unlabeled Examples with Different Data Distributions
- Mining Data Records in Web Pages Department of Computer Science
- Text Classification by Labeling Words , Xiaoli Li
- Intuitive Representation of Decision Trees Using General Rules and Exceptions
- Pruning and Summarizing the Discovered Associations Bing Liu, Wynne Hsu and Yiming Ma
- An EM based training algorithm for Cross-Language Text Categorization Leonardo Rigutini and Marco Maggini
- Analyzing the Subjective Interestingness of Association Rules Bing Liu, Wynne Hsu, Shu Chen and Yiming Ma
- Speed-up Iterative Frequent Itemset Mining with Constraint Changes Gao Cong Bing Liu
- Intelligent Route Finding: Combining Knowledge, Cases and An Efficient Search Algorithm
- Improving an Association Rule Based Classifier Bing Liu, Yiming Ma, and Ching Kian Wong
- Mining Interesting Knowledge Using DMII Bing Liu, Wynne Hsu, Yiming Ma and Shu Chen
- Mining Changes for RealLife Applications Bing Liu, Wynne Hsu, HengSiew Han and Yiyuan Xia
- TupleLevel Analysis for Identification of Interesting Patterns Bing Liu, Wynne Hsu, HingYan Lee * and LaiFun Mun
- Increasing Functional Constraints Need to Be Checked Only Once Department of Information Systems and Computer Science
- An Improved Generic Arc Consistency Algorithm and Its Specializations
- E#ciently Determine the Starting Sample Size for Progressive Sampling
- The Utility of Linguistic Rules in Opinion Mining Xiaowen Ding and Bing Liu
- On the Temporal Dimension of Search Philip S. Yu
- InterestingnessBased Interval Merger for Numeric Association Rules Ke Wang and Soon Hock William Tay and Bing Liu
- Discovering Large Empty Maximal HyperRectangle in MultiDimensional Space
- Semi-Supervised Text Classification Using Partitioned , Wee Sun Lee1
- Sentiment Analysis: A Multi-Faceted Problem Department of Computer Science
- Opinion Observer: Analyzing and Comparing Opinions Department of Computer Science
- Editorial: Special Issue on Web Content Mining Department of Computer Science
- Dealing with Different Distributions in Learning from Positive and Unlabeled Web Data
- Mining Association Rules with Multiple Minimum Supports Bing Liu, Wynne Hsu and Yiming Ma
- Finding Interesting Patterns Using User Expectations Bing Liu, Wynne Hsu, LaiFun Mun, and HingYan Lee *
- Concurrent Discretization of Multiple Attributes Ke Wang and Bing Liu
- Mining Data Records in Web Pages Department of Computer Science
- Mining Topic-Specific Concepts and Definitions Department of Computer Science
- PostAnalysis of Learned Rules Bing Liu and Wynne Hsu
- Extracting Web Data Using Instance-Based Yanhong Zhai and Bing Liu
- SIGKDD Explorations. Copyright 2000 ACM SIGKDD, July 2000. Volume 2, Issue 1 --page 1 Web for Data Mining: Organizing and Interpreting the
- Improving Gender Classification of Blog Authors Arjun Mukherjee Bing Liu
- Sentiment Analysis and Subjectivity Department of Computer Science
- V-Miner: Using Enhanced Parallel Coordinates to Mine Product Design and Test Data 1
- Using Decision Tree Induction for Discovering Holes in Data
- Identifying Comparative Sentences in Text Documents Nitin Jindal and Bing Liu
- Discovering the Set of Fundamental Rule Changes Bing Liu, Wynne Hsu, and Yiming Ma
- Identifying NonActionable Association Rules Bing Liu, Wynne Hsu, and Yiming Ma
- Clustering Through Decision Tree Construction Clustering is an important exploratory data analysis task. It aims to find the intrinsic
- Adding the Temporal Dimension to Search -A Case Study in Publication Search
- Identifying Evaluative Sentences in Online Discussions Zhongwu Zhai
- Identifying Noun Product Features that Imply Opinions Lei Zhang Bing Liu
