Introduction to algorithms
On the complexity of equilibria
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Market Equilibrium via a Primal-Dual-Type Algorithm
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Inapproximability of the kidney exchange problem
Information Processing Letters
Clearing algorithms for barter exchange markets: enabling nationwide kidney exchanges
Proceedings of the 8th ACM conference on Electronic commerce
MarcoPolo: a community system for sharing and integrating travel information on maps
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
On Efficient Recommendations for Online Exchange Markets
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
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Item exchange is becoming a popular behavior and widely supported in more and more online community systems, e. g. online games and social network web sites. Traditional manual search for possible exchange pairs is neither efficient nor effective. Automatic exchange pairing is increasingly demanding in such community systems, and potentially leading to new business opportunities. To meet the needs on item exchange in the market, each user in the system is entitled to list some items he/she no longer needs, as well as some required items he/she is seeking for. Given the values of all items, an exchange between two users is eligible if 1) they both have some unneeded items the other one wants, and 2) the exchange items from both sides are approximately of the same total value. To efficiently support exchange recommendation services, especially with frequent updates on the listed items, new data structures are proposed in this paper to maintain promising exchange pairs for each user. Extensive experiments on both synthetic and real data sets are conducted to evaluate our proposed solutions.