|
ABSTRACT
The access structure, the retrieval model, and the system architecture of the SPIDER information retrieval system are described. The access structure provides efficient weighted retrieval on dynamic data collections. It is based on signatures and non-inverted item descriptions. The signatures provide upper bounds for the exact retrieval status values such that only a small number of exact retrieval status values have to be computed. SPIDER's retrieval model is a probabilistic retrieval model that is capable to exploit the database scheme of semistructured data collections. This model can be considred as a further development of the Binary Independence Indexing (BII) model. The system architecture was derived systematically from a given set of requirements such as effective and efficient retrieval on dynamic data collections, exploitation of the database scheme, computed views, and the integration of information retrieval functionality and database functionality.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
 |
1
|
|
| |
2
|
Birkhoff, G., & Lipson, j. D. (1970). Heterogeneous Algebras. Journal of Combznatorial Theory, 8,115- 133.
|
| |
3
|
CardelIi, L. (1989). Typeful Programming. Technical Report 45, DEC Systems Research Center, Palo Alto.
|
 |
4
|
|
| |
5
|
Chandra, A., &z Harel, D. (1980). Computable Queries for Relational Databases. Journal of Compuler and System Sciences, 21(2),156-178.
|
 |
6
|
|
 |
7
|
Y. Chiaramella , B. Defude , M. F. Bruandet , D. Kerkouba, IOTA: a full text information retrieval system, Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval, p.207-213, September 1986, Palazzo dei Congressi, Pisa, Italy
[doi> 10.1145/253168.253212]
|
 |
8
|
|
 |
9
|
|
 |
10
|
|
 |
11
|
|
| |
12
|
Fret, It. P., & SehKuble, P. (1991a). Designing a Hypermedia Information System, In Karagiannis, D., editor, DEXA '91 Conf., pp. 449-454. Springer-Verlag.
|
| |
13
|
|
| |
14
|
|
| |
15
|
|
 |
16
|
|
 |
17
|
|
| |
18
|
|
 |
19
|
|
| |
20
|
Donna Harman , R. Baeza-Yates , Edward Fox , W. Lee, Inverted files, Information retrieval: data structures and algorithms, Prentice-Hall, Inc., Upper Saddle River, NJ, 1992
|
| |
21
|
|
| |
22
|
|
| |
23
|
Lee, K. F. (September, 1989). Hidden Markov Models: Past, Present, Future. In European Conference on Speech Communication and Technology, pp. 148- 155.
|
| |
24
|
|
 |
25
|
|
| |
26
|
Pogue, C., & Willet, P. (1987). Use of Text Signatures for Document Retrieval in a Highly Parallel Environmen. Parallel Computing, 4(3),259-268.
|
| |
27
|
Robertson, S. E. (1977). The Probability Ranking Principle in IR. Journal of Documentation, 33(4),294- 304.
|
| |
28
|
|
 |
29
|
|
| |
30
|
|
| |
31
|
Sch~iuble, P. (1992). A Tutorial on Information Retrieval. Information Retrieval Course 1991/92, ETH Zurich.
|
| |
32
|
Sch~iuble, P., & Wiithrich, B. (1992). On the Expressive Power of Query Languages. Technical Report 173, ETH Zurich, Department of Computer Science.
|
| |
33
|
|
 |
34
|
|
| |
35
|
|
CITED BY 10
|
|
Klemens Böhm , Adrian Múller , Erich Neuhold, Structured document handling—a case for integrating databases and information retrieval, Proceedings of the third international conference on Information and knowledge management, p.147-154, November 29-December 02, 1994, Gaithersburg, Maryland, United States
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|