Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/38174108-5054-4A25-89F1-56A8E90CA97D | - |
| Identifier | https://doi.org/10.1145/1458469.1458480 | - |
| Language | en | - |
| Title | A measure for cluster cohesion in semantic overlay networks | en |
| Creator | Petrakis Evripidis | en |
| Creator | Πετρακης Ευριπιδης | el |
| Creator | Paraskevi Raftopoulou | en |
| Publisher | Association for Computing Machinery | en |
| Content Summary | Semantic overlay networks cluster peers that are semantically, thematically or socially close into groups by means of a rewiring procedure that is periodically executed by each peer. Rewiring proceeds by establishing new connections to similar peers, and by discarding connections that are outdated or pointing to dissimilar peers. This process aims at improving cluster quality (how well peers with similar content are clustered together) and by this, at improving the flow of information in the network by reducing the number of messages that are exchanged. Therefore, measuring the quality of clustering is an important issue by itself. This is exactly the issue this work is dealing with. In this paper, we introduce a new clustering measure that takes into account the whole neighborhood of a peer (rather than its direct neighbors) thus, providing better insight on the quality of the underlying clustered organisation. Our experimental evaluation with real-word data and queries confirms our assumption that the new measure is better suited for measuring clustering quality than other known measures, such as the (generalised) clustering coefficient. | en |
| Type of Item | Περίληψη Δημοσίευσης σε Συνέδριο | el |
| Type of Item | Conference Paper Abstract | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2015-11-01 | - |
| Date of Publication | 2008 | - |
| Bibliographic Citation | Paraskevi Raftopoulou, Euripides G.M. Petrakis, "A Measure for Cluster Cohesion in Semantic Overlay Networks", in 6th Workshop on Large-Scale Distributed Systems for Information Retrieval (LSDS-IR'08), 2008, pp.59-66. doi:10.1145/1458469.1458480 | en |
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