GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
A genetic algorithm for the generalised assignment problem
Computers and Operations Research
Horting hatches an egg: a new graph-theoretic approach to collaborative filtering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
ACM Computing Surveys (CSUR)
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Search space boundary extension method in real-coded genetic algorithms
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on evolutionary algorithms
Mastering Data Mining: The Art and Science of Customer Relationship Management
Mastering Data Mining: The Art and Science of Customer Relationship Management
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Information Retrieval
Journal of Global Optimization
Multiprocessor Document Allocation: A Genetic Algorithm Approach
IEEE Transactions on Knowledge and Data Engineering
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Multicampaign Assignment Problem
IEEE Transactions on Knowledge and Data Engineering
A Comparison of Collaborative-Filtering Recommendation Algorithms for E-commerce
IEEE Intelligent Systems
A Lagrangian Approach for Multiple Personalized Campaigns
IEEE Transactions on Knowledge and Data Engineering
A novel particle swarm optimization for multiple campaigns assignment problem
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Honey Bee Behavior: A Multi-agent Approach for Multiple Campaigns Assignment Problem
ICIT '08 Proceedings of the 2008 International Conference on Information Technology
International Journal of Electronic Finance
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Within personalized marketing, a recommendation issue known as multicampaign assignment is to overcome a critical problem, known as the multiple recommendation problem which occurs when running several personalized campaigns simultaneously. This paper mainly deals with the hardness of multicampaign assignment, which is treated as a very challenging problem in marketing. The objective in this problem is to find a customer-campaign matrix which maximizes the effectiveness of multiple campaigns under some constraints. We present a realistic response suppression function, which is designed to be more practical, and explain how this can be learned from historical data. Moreover, we provide a proof that this more realistic version of the problem is NP-hard, thus justifying to use of heuristics presented in previous work.