Details
| Original language | English |
|---|---|
| Title of host publication | P2PIR'05 |
| Subtitle of host publication | Proceedings of the 2005 ACM Workshop on Information Retrieval in Peer-to-Peer Networks |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 33-40 |
| Number of pages | 8 |
| ISBN (print) | 1595931643, 9781595931641 |
| Publication status | Published - 4 Nov 2005 |
| Event | P2PIR'05 - 2005 ACM Workshop on Information Retrieval in Peer-to-Peer Networks - Bremen, Germany Duration: 4 Nov 2005 → 4 Nov 2005 |
Publication series
| Name | P2PIR'05 - Proceedings of the 2005 ACM Workshop on Information Retrieval in Peer-to-Peer Networks |
|---|
Abstract
Can we improve P2P search by looking into our social network? In this paper, we argue that P2P networks built upon specific communities (e.g., scientific social networks) could achieve such a goal, by providing an implicit personalization to the output results set. Existing work in social networks investigating co-authorship relations has shown that scientific collaboration networks are scale-free. At the same time, P2P systems based on synthesized small-world networks have emerged, with a positive impact on search efficiency. We propose to use existing social collaboration graphs as foundation for the P2P topology instead of creating purely technological topologies. To get an insight into the relationship between scientific collaboration and co-authorship, we compared both for an existing collaboration network. Based on this analysis, we then generated a large P2P collaboration network derived from co-authorship data collections as basis for our experiments. The most prevalent search type in the scientific context is keyword search for relevant publications. We investigate different search strategies suitable in that context and show our initial experimental results.
Keywords
- Peer-to-peer networks, Query forwarding strategies, Scientific collaboration network analysis
ASJC Scopus subject areas
- Engineering(all)
- General Engineering
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
P2PIR'05: Proceedings of the 2005 ACM Workshop on Information Retrieval in Peer-to-Peer Networks. Association for Computing Machinery (ACM), 2005. p. 33-40 (P2PIR'05 - Proceedings of the 2005 ACM Workshop on Information Retrieval in Peer-to-Peer Networks).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Search strategies for scientific collaboration networks
AU - Chirita, Paul Alexandru
AU - Damian, Andrei
AU - Nejdl, Wolfgang
AU - Siberski, Wolf
PY - 2005/11/4
Y1 - 2005/11/4
N2 - Can we improve P2P search by looking into our social network? In this paper, we argue that P2P networks built upon specific communities (e.g., scientific social networks) could achieve such a goal, by providing an implicit personalization to the output results set. Existing work in social networks investigating co-authorship relations has shown that scientific collaboration networks are scale-free. At the same time, P2P systems based on synthesized small-world networks have emerged, with a positive impact on search efficiency. We propose to use existing social collaboration graphs as foundation for the P2P topology instead of creating purely technological topologies. To get an insight into the relationship between scientific collaboration and co-authorship, we compared both for an existing collaboration network. Based on this analysis, we then generated a large P2P collaboration network derived from co-authorship data collections as basis for our experiments. The most prevalent search type in the scientific context is keyword search for relevant publications. We investigate different search strategies suitable in that context and show our initial experimental results.
AB - Can we improve P2P search by looking into our social network? In this paper, we argue that P2P networks built upon specific communities (e.g., scientific social networks) could achieve such a goal, by providing an implicit personalization to the output results set. Existing work in social networks investigating co-authorship relations has shown that scientific collaboration networks are scale-free. At the same time, P2P systems based on synthesized small-world networks have emerged, with a positive impact on search efficiency. We propose to use existing social collaboration graphs as foundation for the P2P topology instead of creating purely technological topologies. To get an insight into the relationship between scientific collaboration and co-authorship, we compared both for an existing collaboration network. Based on this analysis, we then generated a large P2P collaboration network derived from co-authorship data collections as basis for our experiments. The most prevalent search type in the scientific context is keyword search for relevant publications. We investigate different search strategies suitable in that context and show our initial experimental results.
KW - Peer-to-peer networks
KW - Query forwarding strategies
KW - Scientific collaboration network analysis
UR - http://www.scopus.com/inward/record.url?scp=33749008530&partnerID=8YFLogxK
U2 - 10.1145/1096952.1096959
DO - 10.1145/1096952.1096959
M3 - Conference contribution
AN - SCOPUS:33749008530
SN - 1595931643
SN - 9781595931641
T3 - P2PIR'05 - Proceedings of the 2005 ACM Workshop on Information Retrieval in Peer-to-Peer Networks
SP - 33
EP - 40
BT - P2PIR'05
PB - Association for Computing Machinery (ACM)
T2 - P2PIR'05 - 2005 ACM Workshop on Information Retrieval in Peer-to-Peer Networks
Y2 - 4 November 2005 through 4 November 2005
ER -