Supporting top-K item exchange recommendations in large online communities

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.

Recommending books to be exchanged online in the absence of wish lists

“…A number of item-exchange algorithms have been introduced (Abbassi & Lakshmanan, 2009;Abbassi, Lakshmanan, & Xie, 2013;Su et al, 2012). The exchange algorithm proposed by Abbassi and Lakshmanan (2009) examines two lists, the item list and the wish list, created by each user of popular online community sites, such as Readitswapit, peerflix.com, and swap.com.…”

“…Unlike these strategies that rely on wish lists, EasyEx infers user preferences and suggests books of interest to a user. Contrasting with the tools in Abbassi and Lakshmanan (2009) Abbassi et al (2013) and Su et al (2012), EasyEx does not restrict the exchanges to two users at a time or to short cycles of very few users.…”

“…A number of approaches for item exchange, including book exchanges, have been presented in the literature (Abbassi & Lakshmanan, 2009;Su, Tung, & Zhang, 2012). All of these algorithms, however, require users who participate in the exchange to create and maintain their own wish lists.…”

Optimized Methods to Estimate Lower and Upper Bounds for Approximate Cycle Matching in Homogeneous Symmetric Pub/Sub System

“…In this section, we review some works ( [10], [11], [12], [8], [9], [13]), which are related to cycle matching of Homogeneous Symmetric Pub/Sub System.…”

“…In [13], instead of cycle matching (called circular singleitem exchange model), a Binary Value-based Exchange Model (BVEM) is proposed for one-to-one swap. Each user owns a list of items, and two users are matched if and only if the exchange items from both sides are approximately of the same total value.…”