imrchen profile

Recent Activity

• 05:28: posted Social networks that matter: Twitter under the microscope

• 03:23: posted Fuzzy Systems Design: Social and Engineering Applications (Studies in Fuzziness and Soft Computing)
• 03:21: posted Fuzzy Neural Intelligent Systems: Mathematical Foundation and the Applications in Engineering
• 03:03: posted Fuzzy Set Theory and its Applications

• 07:08: posted Personalized recommendation system based on product specification values

• 03:01: posted Mining Quantitative Association Rules in Large Relational Tables
• 03:00: posted Mining generalized association rules
• 02:59: posted Fast Algorithms for Mining Association Rules
• 02:57: posted Generating Frequent Patterns with the Frequent Pattern List
• 02:54: posted Fast sequential and parallel algorithms for association rule mining: a comparison
• 02:52: posted An Efficient Algorithm for the Incremental Updation of Association Rules in Large Databases
• 02:50: posted Fast Algorithms for Mining Association Rules in Large Databases
• 02:46: posted Discovering Frequent Closed Itemsets for Association Rules
• 02:44: posted Dynamic itemset counting and implication rules for market basket data
• 02:43: posted Mining frequent patterns without candidate generation
• 02:42: posted Turbo-charging vertical mining of large databases
• 02:40: posted Using a hash-based method with transaction trimming for mining association rules
• 02:38: posted Sampling Large Databases for Association Rules
• 02:36: posted LPMiner: an algorithm for finding frequent itemsets using length-decreasing support constraint
• 02:34: posted H-mine: hyper-structure mining of frequent patterns in large databases

• 12:51: posted Mining Sequential Patterns: Generalizations and Performance Improvements
• 12:48: posted Mining Frequent Patterns in Data Streams at Multiple Time Granularities
• 12:36: posted Collaborative Filtering by Personality Diagnosis: A Hybrid Memory-and Model-based Approach
• 12:33: posted Hancock: a language for extracting signatures from data streams
• 10:44: posted Lessons on Applying Automated Recommender Systems to Information-Seeking Tasks
• 09:21: posted A Similarity Measure for Collaborative Filtering with Implicit Feedback
• 08:50: posted Alambic : a privacy-preserving recommender system for electronic commerce
• 08:05: posted Privacy Risks in Recommender Systems
• 08:02: posted The Digitization of Word-of-Mouth: Promise and Challenges of Online Feedback Mechanisms
• 08:01: posted Explaining collaborative filtering recommendations
• 08:00: posted A personal news agent that talks, learns and explains

• 15:06: posted An algorithmic framework for performing collaborative filtering
• 12:59: posted Analysis of recommendation algorithms for e-commerce
• 08:37: posted Recommendation Systems: A Probabilistic Analysis
• 08:29: posted Modeling user rating profiles for collaborative filtering
• 08:25: posted A Maximum Entropy Approach for Collaborative Filtering
• 08:22: posted Collaborative filtering via gaussian probabilistic latent semantic analysis
• 08:20: posted An MDP-Based Recommender System
• 08:05: posted A bayesian model for collaborative filtering
• 07:51: posted Clustering Methods For Collaborative Filtering
• 07:22: posted Using probabilistic relational models for collaborative filtering
• 07:17: posted Learning Collaborative Information Filters
• 06:50: posted Item-based Top-N recommendation algorithms
• 05:33: posted Collaborative Filtering Using Weighted Majority Prediction Algorithms
• 05:30: posted Memory-Based Weighted-Majority Prediction
• 04:43: posted PHOAKS: {A} System for Sharing Recommendations
• 04:42: posted Eigentaste: A Constant Time Collaborative Filtering Algorithm
• 04:21: posted Collaborative Filtering and Inference Rules for Context-Aware Learning Object Recommendation

• 18:19: posted Customer lifetime value modeling and its use for customer retention planning
• 18:15: posted MovieLens Unplugged: Experiences with an Occasionally Connected Recommender System
• 17:39: posted Recommending and evaluating choices in a virtual community of use
• 16:34: posted Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments
• 15:27: posted User Modeling for Adaptive News Access
• 15:17: posted Data Mining
• 15:15: posted Recommendation as classification: using social and content-based information in recommendation
• 15:12: posted Combining collaborative filtering with personal agents for better recommendations
• 14:55: posted A personalized recommender system based on web usage mining and decision tree induction
• 14:23: posted Encyclopedia of library and information science
• 10:04: posted A Framework for Collaborative, Content-Based and Demographic Filtering
• 10:01: posted Methods and metrics for cold-start recommendations
• 09:58: posted Combining content and collaboration in text filtering
• 09:53: posted Combining content-based and collaborative filters in an online newspaper
• 09:08: posted Social Information Filtering: Algorithms for Automating ``Word of Mouth''
• 09:06: posted Novelty and redundancy detection in adaptive filtering
• 09:03: posted Adaptive Lightweight Text Filtering
• 08:59: posted Threshold Setting in Adaptive Filtering
• 08:58: posted Maximum likelihood estimation for filtering thresholds
• 08:28: posted WebWatcher: A Tour Guide for the World Wide Web
• 08:21: posted Information filtering and information retrieval: two sides of the same coin?
• 08:07: posted Human-Computer Collaboration in Recommender Systems
• 08:04: posted Recommender Systems: A GroupLens Perspective
• 07:33: posted Content-based book recommending using learning for text categorization
• 07:22: posted Combining usage, content, and structure data to improve web site recommendation
• 07:22: added a note to Combining usage, content, and structure data to improve web site recommendation
• 07:22: added a note to Combining usage, content, and structure data to improve web site recommendation
• 07:22: added a note to Combining usage, content, and structure data to improve web site recommendation
• 07:22: added a note to Combining usage, content, and structure data to improve web site recommendation
• 07:16: posted Learning and Revising User Profiles: The Identification of Interesting Web Sites
• 07:14: posted {Newsweeder: Learning to filter netnews}
• 07:08: posted Content-boosted collaborative filtering
• 07:05: posted Fab: content-based, collaborative recommendation
• 05:47: posted Marketing Models
• 05:44: posted {The Role of the Management Sciences in Research on Personalization}
• 05:41: posted Automatic text processing
• 04:44: posted Beyond Recommender Systems: Helping People Help Each Other
• 04:27: posted E-Commerce Recommendation Applications

• 13:46: posted GroupLens: Applying Collaborative Filtering to {Usenet} News
• 13:37: posted Study of the usefulness of known and new implicit indicators and their optimal combination for accurate inference of users interests
• 10:07: posted Data Mining Methods and Models
• 10:05: posted Data Mining: Next Generation Challenges and Future Directions (AAAI Press Copublications)
• 10:04: posted Data Mining and Uncertain Reasoning: An Integrated Approach
• 02:17: posted Using Collaborative Filtering to Weave an Information Tapestry
• 02:05: posted Empirical Analysis of Predictive Algorithms for Collaborative Filtering
• 00:57: posted {A probabilistic approach to clustering.}
• 00:55: posted Probabilistic validation approach for clustering
• 00:52: posted Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters

• 23:23: posted Improving the effectiveness of model based recommender systems for highly sparse and noisy Web usage data
• 17:28: posted Algorithms for Clustering Data
• 17:24: posted {Clustering of the self-organizing map}
• 17:21: posted Fuzzy clustering in data mining for telco database marketing campaigns
• 17:19: posted Finding groups in data: an introduction to cluster analysis
• 17:17: posted {Spatial clustering methods in data mining: A survey}
• 17:15: posted Partitioning-based clustering for Web document categorization
• 17:10: posted Automatic subspace clustering of high dimensional data for data mining applications
• 16:57: posted Active Mining
• 16:29: posted {Active Data Mining}
• 14:56: posted Incremental and interactive mining of web traversal patterns
• 14:44: posted The World Wide Web Unleashed
• 14:23: posted Data mining for path traversal patterns in a web environment
• 14:03: posted Generalization and decision tree induction: efficient classification in data mining
• 13:36: posted Applying classification algorithms in practice
• 13:05: posted Machine Learning
• 12:15: posted {Improved decision trees: A generalized version of ID3}
• 12:10: posted A survey of decision tree classifier methodology
• 11:46: posted C4.5: programs for machine learning
• 11:43: posted Learning efficient classification procedures and their application to chess end games
• 11:39: posted Simplifying decision trees
• 11:33: posted Induction of decision trees
• 03:25: posted Attribute-oriented approach for learning classification rules from relational databases
• 03:25: added a note to Attribute-oriented approach for learning classification rules from relational databases
• 03:25: added a note to Attribute-oriented approach for learning classification rules from relational databases
• 03:25: added a note to Attribute-oriented approach for learning classification rules from relational databases
• 03:17: posted Using Multi-Attribute Predicates for Mining Classification Rules
• 03:08: posted SPRINT: {A} Scalable Parallel Classifier for Data Mining
• 03:07: posted Mining Association Rules in Folksonomies
• 03:03: posted An Interval Classifier for Database Mining Applications
• 02:58: posted SLIQ: A Fast Scalable Classifier for Data Mining
• 02:49: posted An Innovative GA-Based Decision Tree Classifier in Large Scale Data Mining
• 02:47: posted Classification and Regression Trees
• 02:35: posted Discovery of Frequent Episodes in Event Sequences
• 02:34: posted Efficient algorithms for discovering association rules

• 14:14: posted From data mining to knowledge discovery: an overview
• 14:13: posted An Overview of Knowledge Discovery in Database: Recent Progress and Challenges
• 14:11: posted Knowledge discovery in databases: an overview
• 07:23: posted Mastering Data Mining: The Art and Science of Customer Relationship Management
• 07:21: posted Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
• 07:18: posted Data Mining, Second Edition, Second Edition : Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems)
• 07:16: posted Intelligent Data Mining: Techniques and Applications (Studies in Computational Intelligence)
• 07:15: posted Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
• 07:09: posted Discovering Knowledge in Data: An Introduction to Data Mining

• 08:28: posted A personalized recommender system for the cosmetic business
• 03:08: posted Bias in the journal impact factor

• 09:37: posted Web 2.0 and beyond: implications for electronic commerce
• 09:37: posted Why share in peer-to-peer networks?
• 09:31: posted Lessons from the Netflix prize challenge
• 09:24: posted Factorization meets the neighborhood: a multifaceted collaborative filtering model
• 09:16: posted Tutorial on recent progress in collaborative filtering
• 08:33: posted A comparative study of fuzzy target selection methods in direct marketing
• 08:31: posted Fuzzy target selection using RFM variables
• 03:54: posted Detection of the customer time-variant pattern for improving recommender systems
• 03:11: posted Getting to know you: learning new user preferences in recommender systems
• 00:36: posted A collaborative filtering-based approach to personalized document clustering
• 00:33: posted Handling sequential pattern decay: Developing a two-stage collaborative recommender system
• 00:29: posted Application of data mining techniques in customer relationship management: A literature review and classification
• 00:05: posted {Impact of Site Characteristics on Recommendation Models Based On Association Rules and Sequential Patterns}
• 00:01: posted The Effect of Behavior Change on Honesty Checking in Peer-to-Peer Systems

• 23:58: posted A lower-bound on the number of rankings required in recommender systems using collaborativ filtering
• 23:57: posted A Recommender Agent for Software Libraries: An Evaluation of Memory-Based and Model-Based Collaborative Filtering
• 23:56: posted Research on Recommendation List Diversity of Recommender Systems
• 23:54: posted An Evaluation Methodology for Collaborative Recommender Systems
• 23:50: posted Learning users' interests by quality classification in market-based recommender systems
• 23:50: posted Attacking Recommender Systems: A Cost-Benefit Analysis
• 23:49: posted A fuzzy linguistic summarization technique for TV recommender systems
• 23:47: posted A movie recommender system based on inductive learning
• 23:47: posted Recommender System Based on Consumer Product Reviews
• 23:45: posted Embedding Emotional Context in Recommender Systems
• 23:43: posted A Study on the Improved Collaborative Filtering Algorithm for Recommender System
• 23:41: posted Recommender Systems
• 23:40: posted Analysis of Trust-Based E-Commerce Recommender Systems Under Recommendation Attacks
• 23:38: posted Employing rough set theory to alleviate the sparsity issue in recommender system
• 23:38: posted Providing Justifications in Recommender Systems
• 23:37: posted Introducing Serendipity in a Content-Based Recommender System
• 10:59: posted Beyond algorithms: An HCI perspective on recommender systems
• 10:14: posted Beyond independent relevance: methods and evaluation metrics for subtopic retrieval
• 09:55: posted {Novelty and topicality in interactive information retrieval}
• 09:54: posted Novelty and diversity in information retrieval evaluation
• 09:46: posted {On the Role of Diversity in Conversational Recommender Systems}
• 09:43: posted Blockbuster Culture's Next Rise or Fall: The Impact of Recommender Systems on Sales Diversity
• 09:25: posted Improving the prediction accuracy of recommendation algorithms: Approaches anchored on human factors
• 09:22: posted Direct Optimization of Ranking Measures
• 08:53: posted Avoiding monotony: improving the diversity of recommendation lists

• 12:03: posted Prediction with Restricted Resources and Finite Automata