@INBOOK{Tempich_05,
    AUTHOR      = {C. Tempich and A. {L\"{o}ser} and J. Heizmann},
    TITLE       = {Community Based Ranking in Peer-to-Peer Networks},
    CHAPTER     = {Lecture Notes in Computer Science},
    PAGES       = {1261--1278},
    PUBLISHER   = {Springer-Verlag GmbH},
    YEAR        = {2005},
    VOLUME      = {3761},
    SERIES      = {},
    ADDRESS     = {},
    EDITION     = {},
    MONTH       = {October},
    NOTE        = {},
    KEY         = {},
    KEYWORDS    = {},
    ISBN        = {},
    URL     ={http://www.springerlink.com/openurl.asp?genre=article&id=doi:10.1007/11575801_21},
    ABSTRACT    = {We address the problem of efficiently ranking the best peers w.r.t. a query with multiple, equally weighted predicates -
    conjunctive queries - in shortcut overlay networks. This problem occurs when routing queries in unstructured peer-to-peer networks, such
    as in peer-to-peer information retrieval applications. Requirements for this task include, e.g., full autonomy of peers as well as full
    control over own resources. Therefore prominent resource location and query routing schemes such as distributed hash tables can not be
    applied in this setting. In order to tackle these requirements we combine a new resource location and query routing approach that exploits
    social metaphors of topical experts and experts¡¯ experts with standard IR measures for ranking peers based on collection-wide information.
    The approach has been fully tested in simulation runs for skewed data distributions and network churn and has been partially implemented
    in the Bibster system.
}, }