Please use this identifier to cite or link to this item:
|Title:||Supporting top-K item exchange recommendations in large online communities|
|Source:||Su, Z.,Tung, A.K.H.,Zhang, Z. (2012). Supporting top-K item exchange recommendations in large online communities. ACM International Conference Proceeding Series : 97-108. ScholarBank@NUS Repository. https://doi.org/10.1145/2247596.2247609|
|Abstract:||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. © 2012 ACM.|
|Source Title:||ACM International Conference Proceeding Series|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 11, 2017
checked on Dec 9, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.