Query reformulation in PDMS based on social relevance

Abstract

We consider peer-to-peer data management systems (PDMS), where each peer maintains mappings between its schema and some acquaintances, along with social links with peer friends. In this context, we deal with reformulating conjunctive queries from a peer’s schema into other peer’s schemas. Precisely, queries against a peer node are rewritten into queries against other nodes using schema mappings thus obtaining query rewritings. Unfortunately, not all the obtained rewritings are relevant to a given query, as the information gain may be negligible or the peer is not worth exploring. On the other hand, the existence of social links with peer friends might be useful to get relevant rewritings. Therefore, we propose a new notion of ‘relevance’ of a query with respect to a mapping that encompasses both a local relevance (the relevance of the query w.r.t. the mapping) and a global relevance (the relevance of the query w.r.t. the entire network). Based on this notion, we have conceived a new query reformulation approach for social PDMS which achieves great accuracy and flexibility. To this purpose, we combine several techniques: (i) social links are expressed as FOAF (Friend of a Friend) links to characterize peer’s friendship; (ii) concise mapping summaries are used to obtain mapping descriptions; (iii) local semantic views (LSV) are special views that contain information about mappings captured from the network by using gossiping techniques. Our experimental evaluation, based on a prototype on top of PeerSim and a simulated network demonstrate that our solution yields greater recall, compared to traditional query translation approaches proposed in the literature.