Details
| Original language | English |
|---|---|
| Title of host publication | Semantic Desktop Workshop |
| Subtitle of host publication | Proceedings of the ISWC 2005 Workshop on The Semantic Desktop - Next Generation Information Management & Collaboration Infrastructure |
| Publication status | Published - 2005 |
| Event | Workshop on the Semantic Desktop - Next Generation Information Management and Collaboration Infrastructure, ISWC 2005 - Galway, Ireland Duration: 6 Nov 2005 → 6 Nov 2005 |
Publication series
| Name | CEUR Workshop Proceedings |
|---|---|
| Publisher | CEUR Workshop Proceedings |
| Volume | 175 |
| ISSN (Print) | 1613-0073 |
Abstract
Existing desktop search applications, trying to keep up with the rapidly increasing storage capacities of our hard disks, offer an incomplete solution for the information retrieval. In this paper we describe our desktop search prototype, which enhances conventional full-text search with semantics and ranking modules. In this prototype we extract and store activity-based metadata explicitly as RDF annotations. Our main contributions are represented by the 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. The initially disconnected sets of resources on the desktop are connected by our contextual metadata, and then a PageRank derived algorithm allows us to rank these resources appropriately. Finally, we use a detailed working scenario to discuss the advantages of this approach, as well as the user interfaces of our search prototype.
ASJC Scopus subject areas
- Computer Science(all)
- General Computer Science
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Semantic Desktop Workshop: Proceedings of the ISWC 2005 Workshop on The Semantic Desktop - Next Generation Information Management & Collaboration Infrastructure. 2005. 7 (CEUR Workshop Proceedings; Vol. 175).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Semantically enhanced searching and ranking on the desktop
AU - Chirita, Paul Alexandru
AU - Ghita, Stefania
AU - Nejdl, Wolfgang
AU - Paiu, Raluca
PY - 2005
Y1 - 2005
N2 - Existing desktop search applications, trying to keep up with the rapidly increasing storage capacities of our hard disks, offer an incomplete solution for the information retrieval. In this paper we describe our desktop search prototype, which enhances conventional full-text search with semantics and ranking modules. In this prototype we extract and store activity-based metadata explicitly as RDF annotations. Our main contributions are represented by the 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. The initially disconnected sets of resources on the desktop are connected by our contextual metadata, and then a PageRank derived algorithm allows us to rank these resources appropriately. Finally, we use a detailed working scenario to discuss the advantages of this approach, as well as the user interfaces of our search prototype.
AB - Existing desktop search applications, trying to keep up with the rapidly increasing storage capacities of our hard disks, offer an incomplete solution for the information retrieval. In this paper we describe our desktop search prototype, which enhances conventional full-text search with semantics and ranking modules. In this prototype we extract and store activity-based metadata explicitly as RDF annotations. Our main contributions are represented by the 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. The initially disconnected sets of resources on the desktop are connected by our contextual metadata, and then a PageRank derived algorithm allows us to rank these resources appropriately. Finally, we use a detailed working scenario to discuss the advantages of this approach, as well as the user interfaces of our search prototype.
UR - http://www.scopus.com/inward/record.url?scp=84883479940&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84883479940
T3 - CEUR Workshop Proceedings
BT - Semantic Desktop Workshop
T2 - Workshop on the Semantic Desktop - Next Generation Information Management and Collaboration Infrastructure, ISWC 2005
Y2 - 6 November 2005 through 6 November 2005
ER -