Gal A. Kaminka's Publications

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PHIRST: A Distributed Architecture for P2P Information Retrieval

Avi Rosenfeld, Sarit Kraus, Gal A. Kaminka, and Claudia V. Goldman. PHIRST: A Distributed Architecture for P2P Information Retrieval. Information Systems, 34(2):290–303, Elsevier Science, 2009.

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Abstract

Recent advances in peer to peer (P2P) search algorithms have presented viable structured and unstructured approaches for full-text search. We posit that these existing approaches are each best suited for different types of queries. We present PHIRST, the first system to facilitate effective full-text search within P2P databases. PHIRST works by effectively leveraging the relative strengths of these approaches. Similar to structured approaches, agents first publish terms within their stored documents. However, frequent terms are quickly identified and not exhaustively stored, resulting in a significant reduction in the system’s storage requirements. During query lookup, agents use unstructured searches to compensate for the lack of fully published terms. Additionally, they explicitly weigh between the costs involved with structured and unstructured approaches, allowing for a significant reduction in query costs. Finally, the reduction in storage requirements becomes more significant when redundant copies of data are required to handle node failures. We evaluated the effectiveness of our approach using both real-world and artificial queries. We found that in most situations our approach yields near perfect recall. We discuss the limitations of our system, as well as possible compensatory strategies.

Additional Information

The article's official web page is at: http://dx.doi.org/10.1016/j.is.2008.08.002.

BibTeX

@Article{avip2p,
author = {Avi Rosenfeld and Sarit Kraus and Gal A. Kaminka and Claudia V. Goldman},
title = {{PHIRST}: A Distributed Architecture for {P2P} Information Retrieval},
journal = {Information Systems},
year = {2009},
OPTkey = {},
volume = {34},
number = {2},
pages = {290--303},
OPTmonth = {},
publisher = {Elsevier Science},
OPTnote = {},
abstract = {
 Recent advances in peer to peer (P2P) search algorithms have presented viable structured and 
unstructured approaches for full-text search. We posit that these existing approaches are each best 
suited for different types of queries. We present PHIRST, the first system to facilitate effective  full-text search within P2P databases. PHIRST works by effectively leveraging the relative 
strengths of these approaches. Similar to structured approaches, agents first publish terms within 
their stored documents. However, frequent terms are quickly identified and not exhaustively stored, 
resulting in a significant reduction in the system’s storage requirements. During query lookup, agents 
use unstructured searches to compensate for the lack of fully published terms. Additionally, they 
explicitly weigh between the costs involved with structured and unstructured approaches, allowing 
for a significant reduction in query costs. Finally, the reduction in storage requirements becomes 
more significant when redundant copies of data are required to handle node failures. We evaluated 
the effectiveness of our approach using both real-world and artificial queries. We found that in most 
situations our approach yields near perfect recall. We discuss the limitations of our system, as well 
as possible compensatory strategies.
},
 OPTannote = {}
}

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