Abstract
| Original language | English |
|---|---|
| Title of host publication | Intelligent Search on XML Data: Applications, Languages, Models, Implementations, and Benchmarks |
| Editors | Henk Blanken, T. Grabs, H-J. Schek, R. Schenkel, G. Weikum |
| Place of Publication | Berlin, Germany |
| Publisher | Springer |
| Pages | 179-191 |
| Number of pages | 15 |
| ISBN (Electronic) | 978-3-540-45194-5 |
| ISBN (Print) | 978-3-540-40768-3 |
| DOIs | |
| Publication status | Published - 2003 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer |
| Volume | 2818 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Fingerprint
Keywords
- IR-63669
- EWI-8102
- DB-XMLDB: XML DATABASES
- DB-XMLIR: XML INFORMATION RETRIEVAL
- DB-PRJMOA: MAGNUM OBJECT ALGEBRA
- METIS-216058
Cite this
}
The Multi-model DBMS Architecture and XML Information Retrieval. / de Vries, A.P.; List, J.A.; Blok, H.E.
Intelligent Search on XML Data: Applications, Languages, Models, Implementations, and Benchmarks. ed. / Henk Blanken; T. Grabs; H-J. Schek; R. Schenkel; G. Weikum. Berlin, Germany : Springer, 2003. p. 179-191 (Lecture Notes in Computer Science; Vol. 2818).Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review
TY - CHAP
T1 - The Multi-model DBMS Architecture and XML Information Retrieval
AU - de Vries, A.P.
AU - List, J.A.
AU - Blok, H.E.
PY - 2003
Y1 - 2003
N2 - Since long, computer science has distinguished between information retrieval and data retrieval, where information retrieval entails the problem of ranking textual documents on their content (with the goal to identify documents relevant for satisfying a user's information need) while data retrieval involves exact match, that is, checking a data collection for presence or absence of (precisely specified) items. But, now that XML has become a standard document model that allows structure and text content to be represented in a combined way, new generations of information retrieval systems are expected to handle semi-structured documents instead of plain text, with usage scenarios that require the combination of `conventional' ranking with other query constraints; based on the structure of text documents, on the information extracted from various media (or various media representations), or through additional information induced during the query process.
AB - Since long, computer science has distinguished between information retrieval and data retrieval, where information retrieval entails the problem of ranking textual documents on their content (with the goal to identify documents relevant for satisfying a user's information need) while data retrieval involves exact match, that is, checking a data collection for presence or absence of (precisely specified) items. But, now that XML has become a standard document model that allows structure and text content to be represented in a combined way, new generations of information retrieval systems are expected to handle semi-structured documents instead of plain text, with usage scenarios that require the combination of `conventional' ranking with other query constraints; based on the structure of text documents, on the information extracted from various media (or various media representations), or through additional information induced during the query process.
KW - IR-63669
KW - EWI-8102
KW - DB-XMLDB: XML DATABASES
KW - DB-XMLIR: XML INFORMATION RETRIEVAL
KW - DB-PRJMOA: MAGNUM OBJECT ALGEBRA
KW - METIS-216058
U2 - 10.1007/978-3-540-45194-5_12
DO - 10.1007/978-3-540-45194-5_12
M3 - Chapter
SN - 978-3-540-40768-3
T3 - Lecture Notes in Computer Science
SP - 179
EP - 191
BT - Intelligent Search on XML Data: Applications, Languages, Models, Implementations, and Benchmarks
A2 - Blanken, Henk
A2 - Grabs, T.
A2 - Schek, H-J.
A2 - Schenkel, R.
A2 - Weikum, G.
PB - Springer
CY - Berlin, Germany
ER -