ACM Home Page
Please provide us with feedback. Feedback
Optimizing queries over multimedia repositories
Full text PdfPdf (1.36 MB)
Source International Conference on Management of Data archive
Proceedings of the 1996 ACM SIGMOD international conference on Management of data table of contents
Montreal, Quebec, Canada
Pages: 91 - 102  
Year of Publication: 1996
ISBN:0-89791-794-4
Also published in ...
Authors
Surajit Chaudhuri  Microsoft Research and Hewlett-Packard Laboratories
Luis Gravano  Hewlett-Packard Laboratories, Stanford University
Sponsors
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 26,   Citation Count: 37
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/233269.233323
What is a DOI?

ABSTRACT

Repositories of multimedia objects having multiple types of attributes (e.g., image, text) are becoming increasingly common. A selection on these attributes will typically produce not just a set of objects, as in the traditional relational query model (filtering), but also a grade of match associated with each object, indicating how well the object matches the selection condition (ranking). Also, multimedia repositories may allow access to the attributes of each object only through indexes. We investigate how to optimize the processing of queries over multimedia repositories. A key issue is the choice of the indexes used to search the repository. We define an execution space that is search-minimal, i.e., the set of indexes searched is minimal. Although the general problem of picking an optimal plan in the search-minimal execution space is NP-hard, we solve the problem efficiently when the predicates in the query are independent. We also show that the problem of optimizing queries that ask for a few top-ranked objects can be viewed, in many cases, as that of evaluating selection conditions. Thus, both problems can be viewed together as an extended filtering problem.


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
Surajit Chaudhuri and Luis Gravano. Optimizing queries over multimedia repositories. Technical report, Hewlett-Packard Laboratories, March 1996. Also available as ftp://db.stanford.edu/pub/gravano/- 1996/s ~gmod. ps.
 
3
 
4
W. Niblack, R. Barber, W. Equitz, h/i. Flickner, E. Glasman, D. Petkovic, P. Yanker, and C. Faloutsos. The QBIC project: Querying images by content using color, texture, and shape. In Storage and retrieval }or zmage and video databases (SPIE), pages 173-187, February 1993.
 
5
6
7
 
8
9
10
 
11
12
13
 
14
 
15
16
17
18
 
19
20
 
21
22
 
23

CITED BY  37

Collaborative Colleagues:
Surajit Chaudhuri: colleagues
Luis Gravano: colleagues