Applying Cross-Level Association Rule Mining to Cold-Start Recommendations

No abstract is available for this paper.

• Publication year

  2007

• Venue

  2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops

• Publication date

  2007-11-02

• Fields of study

  Computer Science

• Identifiers
  DOI 10.5555/1339264.1339676
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• A New Collaborative Recommender System Addressing Three Problems

  2004cited by this paper
• Efficient Adaptive-Support Association Rule Mining for Recommender Systems

  2004cited by this paper
• Content-Boosted Collaborative Filtering

  2001cited by this paper
• Categories and Subject Descriptors

  2001cited by this paper
• Mining Frequent Itemsets Using Support Constraints

  2000cited by this paper
• Mining Multiple-Level Association Rules in Large Databases

  1999cited by this paper
• Empirical Analysis of Predictive Algorithms for Collaborative Filtering

  1998cited by this paper
• GroupLens: applying collaborative filtering to Usenet news

  1997cited by this paper
• Mining association rules between sets of items in large databases

  1993cited by this paper

• A Comprehensive Survey on Cross-Domain Recommendation: Taxonomy, Progress, and Prospects

  2025influential citation
• MARCO: A Cooperative Knowledge Transfer Framework for Personalized Cross-domain Recommendations

  2025cites this paper
• Amazon-KG: A Knowledge Graph Enhanced Cross-Domain Recommendation Dataset

  2024cites this paper
• Cold Start Problem in Recommendation System: A Solution Model Based on Clustering and Association Rule Techniques

  2022cites this paper
• The Cold-start Problem: Minimal Users' Activity Estimation

  2021cites this paper
• Cross-Domain Recommendation: Challenges, Progress, and Prospects

  2021cites this paper
• Understanding Shopping Behaviors With Category- and Brand-Level Market Basket Analysis

  2020cites this paper
• Movie Recommendation System Based on Users' Personal Information and Movies Rated Using the Method of k-Clique and Normalized Discounted Cumulative Gain

  2020cites this paper
• Personalized Movie Recommendation System Combining Data Mining with the k-Clique Method

  2019cites this paper
• Tag-Based Recommender Systems

  2018cites this paper
• AN UNDERSTANDING AND APPROACH SOLUTION FOR COLD START PROBLEM ASSOCIATED WITH RECOMMENDER SYSTEM : A LITERATURE REVIEW

  2018cites this paper
• Addressing cold start problem through unfavorable reviews and specification of products in recommender system

  2017cites this paper
• Three essays on audit technology: audit 4.0, blockchain, and audit app

  2017cites this paper
• Universatile Learning Engine Inspired by IID-Collaboartive Filtering and Adaptive Learning

  2017cites this paper
• Music Recommendation System Using Association Rule Mining and Clustering Technique To Address Coldstart Problem

  2014cites this paper
• Recommending user connections by utilising the real-time Web

  2014cites this paper
• A Survey on Recommender Systems based on Collaborative Filtering Technique

  2013cites this paper
• Integrating Collaborative Filtering and Matching-based Search for Product Recommendations

  2013cites this paper
• Addressing cold start problem in recommender systems using association rules and clustering technique

  2013cites this paper
• A Hybrid Approach to Solve Cold Start Problem in Recommender Systems using Association Rules and Clustering Technique

  2013cites this paper
• Enhancing collaborative filtering recommendations by utilizing multi-objective particle swarm optimization embedded association rule mining

  2013cites this paper
• Using profile expansion techniques to alleviate the new user problem

  2013cites this paper
• Reduction of Data Sparsity in Collaborative Filtering based on Fuzzy Inference Rules

  2013cites this paper
• Enhanced New User Recommendations based on Quantitative Association Rule Mining

  2012cites this paper
• Fuzzy Computational Ontologies in Contexts

  2012cites this paper
• International Conference on Ambient Systems , Networks and Technologies ( ANT ) Enhanced New User Recommendations based on Quantitative Association Rule Mining

  2012cites this paper
• Exploiting Formal Concept Analysis in a Customizing Recommendation for New User and Gray Sheep Problems

  2012cites this paper
• A weighted-graph based approach for solving the cold start problem in collaborative recommender systems

  2012cites this paper
• A Distributed, Architecture-Centric Approach to Computing Accurate Recommendations from Very Large and Sparse Datasets

  2011cites this paper
• Addressing the cold start problem in tag-based recommender systems

  2011cites this paper
• A Scalable Tag-Based Recommender System for New Users of the Social Web

  2011cites this paper
• Nouvelle Approche à base de Graphes pour les Systèmes de Recommandation Collaboratifs

  2011cites this paper
• Recommender Systems for Human Resources Task Assignment

  2010cites this paper
• Using linguistic incomplete preference relations to cold start recommendations

  2010cites this paper
• Using Association Rules to Solve the Cold-Start Problem in Recommender Systems

  2010cites this paper
• Probabilistic neural network approach to alleviate sparsity and cold start problems in collaborative recommender systems

  2010cites this paper
• Mining Abstract Highly Correlated Pairs

  2009cites this paper
• Incomplete preference relations to smooth out the cold-start in collaborative Recommender Systems

  2009cites this paper
• An empirical study of a cross-level association rule mining approach to cold-start recommendations

  2008cites this paper
• Dimensionality reduction algorithms with applications to collaborative data and images

  2008cites this paper
• Chapter 9 Applications 9.1 Overview 9.1.1 Motivation

  year unknowncites this paper