Abstract

This paper experimentally studies approaches to the problem of describing heterogeneous information sources in distributed environments. In particular, we consider a scenario where a large number of end users can share and retrieve text documents over a peer-to-peer network. Descriptions (or profiles) of peers are useful in a number of applications, such as query routing, overlay construction and expert search. The approach proposed in this paper introduces a new learning method that boosts the weight of query terms in a peer's profile when the peer provides useful documents w.r.t. a given query. Experimental results show high potential for this method. Therefore, various extensions are proposed that involve more user interaction.

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Cite this article

@article{cai-11049,
  author  = {Hans Friedrich Witschel},
  title   = {Learning Profiles for Heterogeneous Distributed Information Sources},
  journal = {Computing and Informatics},
  volume  = {29},
  number  = {4},
  pages   = {571--584},
  year    = {2010},
  issn    = {1335-9150},
  url     = {https://cai.type.sk/content/2010/4/learning-profiles-for-heterogeneous-distributed-information-sources/}
}
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