Name
Abstract | ||
|---|---|---|
We describe an efficient peer-to-peer information retrieval system, pSearch; that supports state-of-the-art content- and semantic-based full-text searches. pSearch avoids the scalability problem of existing systems that employ centralized indexing, or index/query flooding. It also avoids the nondeterminism that is exhibited by heuristic-based approaches. In pSearch; documents in the network are organized around their vector representations (based on modern document ranking algorithms) such that the search space for a given query is organized around related documents, achieving both efficiency and accuracy. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1145/774763.774777 | Computer Communication Review |
Keywords | Field | DocType |
heuristic-based approach,scalability problem,structured overlay,efficient peer-to-peer information retrieval,centralized indexing,search space,modern document,related document,ranking algorithm,psearch avoids,query flooding,indexation,information retrieval system,information retrieval | Internet topology,Learning to rank,Data mining,Heuristic,Information retrieval,Computer science,Highly optimized tolerance,Search engine indexing,Robustness (computer science),Ranking (information retrieval),Scalability | Journal |
Volume | Issue | ISSN |
33 | 1 | 0146-4833 |
Citations | PageRank | References |
108 | 9.34 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chunqiang Tang | 1 | 1287 | 75.09 |
| Zhichen Xu | 2 | 1057 | 66.72 |
| Mallik Mahalingam | 3 | 194 | 14.52 |