Supporting ranked Boolean similarity queries in MARS

Michael Ortega; Yong Rui; Kaushik Chakrabarti; Kriengkrai Porkaew; Sharad Mehrotra; Thomas S. Huang

doi:10.1109/69.738357

Supporting ranked Boolean similarity queries in MARS

Michael Ortega, Yong Rui, Kaushik Chakrabarti, Kriengkrai Porkaew, Sharad Mehrotra, Thomas S. Huang

Coordinated Science Lab

Research output: Contribution to journal › Article › peer-review

Abstract

To address the emerging needs of applications that require access to and retrieval of multimedia objects, we are developing the Multimedia Analysis and Retrieval System (MARS) [29]. In this paper, we concentrate on the retrieval subsystem of MARS and its support for content-based queries over image databases. Content-based retrieval techniques have been extensively studied for textual documents in the area of automatic information retrieval [40], [4]. This paper describes how these techniques can be adapted for ranked retrieval over image databases. Specifically, we discuss the ranking and retrieval algorithms developed in MARS based on the Boolean retrieval model and describe the results of our experiments that demonstrate the effectiveness of the developed model for image retrieval.

Original language	English (US)
Pages (from-to)	905-925
Number of pages	21
Journal	IEEE Transactions on Knowledge and Data Engineering
Volume	10
Issue number	6
DOIs	https://doi.org/10.1109/69.738357
State	Published - 1998

Keywords

Boolean queries
Database management
Incremental query processing
Multimedia retrieval
Ranked retrieval

ASJC Scopus subject areas

Information Systems
Computer Science Applications
Computational Theory and Mathematics

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title = "Supporting ranked Boolean similarity queries in MARS",

abstract = "To address the emerging needs of applications that require access to and retrieval of multimedia objects, we are developing the Multimedia Analysis and Retrieval System (MARS) [29]. In this paper, we concentrate on the retrieval subsystem of MARS and its support for content-based queries over image databases. Content-based retrieval techniques have been extensively studied for textual documents in the area of automatic information retrieval [40], [4]. This paper describes how these techniques can be adapted for ranked retrieval over image databases. Specifically, we discuss the ranking and retrieval algorithms developed in MARS based on the Boolean retrieval model and describe the results of our experiments that demonstrate the effectiveness of the developed model for image retrieval.",

keywords = "Boolean queries, Database management, Incremental query processing, Multimedia retrieval, Ranked retrieval",

author = "Michael Ortega and Yong Rui and Kaushik Chakrabarti and Kriengkrai Porkaew and Sharad Mehrotra and Huang, {Thomas S.}",

note = "Funding Information: This work was supported by the National Science Foundation CAREER Award No. 11s-9734300; in part by NSF CISE Research Infrastructure Grant No. CDA-9624396; and in part by the Army Research Laboratory under Cooperative Agreement No. DAAL01-96-2-0003. Michael Ortega is also supported, in part, by CONACYT Grant No. 89061. Yong Rui is also supported, in part, by thle Department of Computer Science and Engineering in the College of Engineering at the University of Illinois at Urbana-Champaign.",

year = "1998",

doi = "10.1109/69.738357",

language = "English (US)",

volume = "10",

pages = "905--925",

journal = "IEEE Transactions on Knowledge and Data Engineering",

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publisher = "IEEE Computer Society",

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AU - Ortega, Michael

AU - Rui, Yong

AU - Chakrabarti, Kaushik

AU - Porkaew, Kriengkrai

AU - Mehrotra, Sharad

AU - Huang, Thomas S.

N1 - Funding Information: This work was supported by the National Science Foundation CAREER Award No. 11s-9734300; in part by NSF CISE Research Infrastructure Grant No. CDA-9624396; and in part by the Army Research Laboratory under Cooperative Agreement No. DAAL01-96-2-0003. Michael Ortega is also supported, in part, by CONACYT Grant No. 89061. Yong Rui is also supported, in part, by thle Department of Computer Science and Engineering in the College of Engineering at the University of Illinois at Urbana-Champaign.

PY - 1998

Y1 - 1998

N2 - To address the emerging needs of applications that require access to and retrieval of multimedia objects, we are developing the Multimedia Analysis and Retrieval System (MARS) [29]. In this paper, we concentrate on the retrieval subsystem of MARS and its support for content-based queries over image databases. Content-based retrieval techniques have been extensively studied for textual documents in the area of automatic information retrieval [40], [4]. This paper describes how these techniques can be adapted for ranked retrieval over image databases. Specifically, we discuss the ranking and retrieval algorithms developed in MARS based on the Boolean retrieval model and describe the results of our experiments that demonstrate the effectiveness of the developed model for image retrieval.

AB - To address the emerging needs of applications that require access to and retrieval of multimedia objects, we are developing the Multimedia Analysis and Retrieval System (MARS) [29]. In this paper, we concentrate on the retrieval subsystem of MARS and its support for content-based queries over image databases. Content-based retrieval techniques have been extensively studied for textual documents in the area of automatic information retrieval [40], [4]. This paper describes how these techniques can be adapted for ranked retrieval over image databases. Specifically, we discuss the ranking and retrieval algorithms developed in MARS based on the Boolean retrieval model and describe the results of our experiments that demonstrate the effectiveness of the developed model for image retrieval.

KW - Boolean queries

KW - Database management

KW - Incremental query processing

KW - Multimedia retrieval

KW - Ranked retrieval

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Supporting ranked Boolean similarity queries in MARS

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Keywords

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