Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
The role of transparency in recommender systems
CHI '02 Extended Abstracts on Human Factors in Computing Systems
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Time weight collaborative filtering
Proceedings of the 14th ACM international conference on Information and knowledge management
Scalable and near real-time burst detection from eCommerce queries
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Inferring semantic query relations from collective user behavior
Proceedings of the 17th ACM conference on Information and knowledge management
The Unreasonable Effectiveness of Data
IEEE Intelligent Systems
Collaborative filtering with temporal dynamics
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Substitutes or complements: another step forward in recommendations
Proceedings of the 10th ACM conference on Electronic commerce
The million dollar programming prize
IEEE Spectrum
Topic modeling for personalized recommendation of volatile items
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Recommender Systems Handbook
User behavior in zero-recall ecommerce queries
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Recommending ephemeral items at web scale
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Utilizing related products for post-purchase recommendation in e-commerce
Proceedings of the fifth ACM conference on Recommender systems
Rewriting null e-commerce queries to recommend products
Proceedings of the 21st international conference companion on World Wide Web
Implementation of Context-Aware Item Recommendation through MapReduce Data Aggregation
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
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Recommender systems form the core of e-commerce systems. In this paper we take a top-down view of recommender systems and identify challenges, opportunities, and approaches in building recommender systems for a marketplace platform. We use eBay as an example where the elaborate interaction offers a number opportunities for creative recommendations. However, eBay also poses complexities resulting from high sparsity of relationships. Our discussion can be generalized beyond eBay to other marketplaces.