Test-bed building process for context-aware peer-to-peer information retrieval evaluation

Abstract

With the rapid growth of information rate in the web, it is of paramount importance to develop scalable information retrieval approaches. These approaches are based on distributed information retrieval systems. Likewise, the emergence of contextual information retrieval has introduced the research personalisation which attempts to reduce the research ambiguity and to return most appropriate information to the user. Therefore, it seems a compelling issue, to implement techniques related to contextual peer-to-peer information retrieval (P2P-IR) to better exploit the personalisation of information in order to achieve a more efficient access to data. In this respect, evaluating these approaches in contextual P2P-IR is a crucial step. Indeed, to the best of our knowledge, there is no available test-beds dedicated to the evaluation of contextual P2P-IR. In particular, we propose, two methods. The first is based on existing collections that are enriched with external semantic resources. The second offers the possibility to build test-beds from multiple sources data.