Details
| Original language | English |
|---|---|
| Title of host publication | The Semantic Web |
| Subtitle of host publication | Research and Applications: 3rd European Semantic Web Conference, ESWC 2006 Proceedings |
| Publisher | Springer Verlag |
| Pages | 348-362 |
| Number of pages | 15 |
| ISBN (electronic) | 978-3-540-34545-9 |
| ISBN (print) | 978-3-540-34544-2 |
| Publication status | Published - 2006 |
| Event | 3rd European Semantic Web Conference (ESWC 2006) - Budva Duration: 11 Jun 2006 → 14 Jun 2006 Conference number: 3 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 4011 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
Existing desktop search applications, trying to keep up with the rapidly increasing storage capacities of our hard disks, offer an incomplete solution for information retrieval. In this paper we describe our Beagle- desktop search prototype, which enhances conventional fulltext search with semantics and ranking modules. This prototype extracts and stores activity-based metadata explicitly as RDF annotations. Our main contributions are extensions we integrate into the Beagle desktop search infrastructure to exploit this additional contextual information for searching and ranking the resources on the desktop. Contextual information plus ranking brings desktop search much closer to the performance of web search engines. Initially disconnected sets of resources on the desktop are connected by our contextual metadata, PageRank derived algorithms allow us to rank these resources appropriately. First experiments investigating precision and recall quality of our search prototype show encouraging improvements over standard search.
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
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The Semantic Web: Research and Applications: 3rd European Semantic Web Conference, ESWC 2006 Proceedings. Springer Verlag, 2006. p. 348-362 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4011 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Beagle++
T2 - 3rd European Semantic Web Conference (ESWC 2006)
AU - Chirita, Paul Alexandru
AU - Costache, Stefania
AU - Nejdl, Wolfgang
AU - Paiu, Raluca
N1 - Conference code: 3
PY - 2006
Y1 - 2006
N2 - Existing desktop search applications, trying to keep up with the rapidly increasing storage capacities of our hard disks, offer an incomplete solution for information retrieval. In this paper we describe our Beagle- desktop search prototype, which enhances conventional fulltext search with semantics and ranking modules. This prototype extracts and stores activity-based metadata explicitly as RDF annotations. Our main contributions are extensions we integrate into the Beagle desktop search infrastructure to exploit this additional contextual information for searching and ranking the resources on the desktop. Contextual information plus ranking brings desktop search much closer to the performance of web search engines. Initially disconnected sets of resources on the desktop are connected by our contextual metadata, PageRank derived algorithms allow us to rank these resources appropriately. First experiments investigating precision and recall quality of our search prototype show encouraging improvements over standard search.
AB - Existing desktop search applications, trying to keep up with the rapidly increasing storage capacities of our hard disks, offer an incomplete solution for information retrieval. In this paper we describe our Beagle- desktop search prototype, which enhances conventional fulltext search with semantics and ranking modules. This prototype extracts and stores activity-based metadata explicitly as RDF annotations. Our main contributions are extensions we integrate into the Beagle desktop search infrastructure to exploit this additional contextual information for searching and ranking the resources on the desktop. Contextual information plus ranking brings desktop search much closer to the performance of web search engines. Initially disconnected sets of resources on the desktop are connected by our contextual metadata, PageRank derived algorithms allow us to rank these resources appropriately. First experiments investigating precision and recall quality of our search prototype show encouraging improvements over standard search.
UR - http://www.scopus.com/inward/record.url?scp=33746045244&partnerID=8YFLogxK
U2 - 10.1007/11762256_27
DO - 10.1007/11762256_27
M3 - Conference contribution
AN - SCOPUS:33746045244
SN - 978-3-540-34544-2
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 348
EP - 362
BT - The Semantic Web
PB - Springer Verlag
Y2 - 11 June 2006 through 14 June 2006
ER -