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Ranked search over structured and se...

Guo, Lin.

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Ranked search over structured and semi-structured data.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Ranked search over structured and semi-structured data./
Author:	Guo, Lin.
Description:	161 p.
Notes:	Adviser: Jayavel Shanmugasundaram.
Contained By:	Dissertation Abstracts International68-08B.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3276833
ISBN:	9780549199007

Ranked search over structured and semi-structured data.
Guo, Lin.

Ranked search over structured and semi-structured data. - 161 p.

Adviser: Jayavel Shanmugasundaram.

Thesis (Ph.D.)--Cornell University, 2007.

Traditionally, relational database systems have been designed for precise queries over structured data, while information retrieval systems have been designed for more flexible ranked keyword search queries over unstructured (text) data. However, many new and emerging applications require data management capabilities that combine the benefits of database and information retrieval systems, e.g., e-commerce and content management applications. In this dissertation, we have proposed and initiated steps toward the larger goal of integrating relational database and information retrieval systems.

ISBN: 9780549199007Subjects--Topical Terms:

626642
Computer Science.

Ranked search over structured and semi-structured data.
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020 $a 9780549199007
035 $a (UMI)AAI3276833
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040 $a UMI $c UMI
100 1 $a Guo, Lin. $3 1280973
245 1 0 $a Ranked search over structured and semi-structured data.
300 $a 161 p.
500 $a Adviser: Jayavel Shanmugasundaram.
500 $a Source: Dissertation Abstracts International, Volume: 68-08, Section: B, page: 5352.
502 $a Thesis (Ph.D.)--Cornell University, 2007.
520 $a Traditionally, relational database systems have been designed for precise queries over structured data, while information retrieval systems have been designed for more flexible ranked keyword search queries over unstructured (text) data. However, many new and emerging applications require data management capabilities that combine the benefits of database and information retrieval systems, e.g., e-commerce and content management applications. In this dissertation, we have proposed and initiated steps toward the larger goal of integrating relational database and information retrieval systems.
520 $a First, we consider the problem of ranked text search in relational databases, where the traditional ranking paradigms and techniques developed for stand-alone unstructured documents are not directly applicable. We thus propose a new ranking paradigm that uses structured data values to score the results of text search queries. Our experimental results on real and synthetic data sets show that we can support the new ranking paradigm efficiently in relational databases.
520 $a Second, we explore a novel problem of discovering rich relationships in databases based on user queries with text search and structural query conditions. Toward this end, we have introduced the notion of data, topology and developed efficient algorithms for computing ranked topologies based on user queries. We have evaluated our algorithms using a real biological database, the Biozon database (http://www.biozon.org).
520 $a Third, we consider the problem of efficiently producing results for keyword search queries over semi-structured XML documents. We present the XRANK system that is built to address the novel challenges for effective XML keyword search as apposed to HTML keyword search. Our experimental results show that XRANK offers both space and performance benefits when compared with existing approaches.
590 $a School code: 0058.
650 4 $a Computer Science. $3 626642
690 $a 0984
710 2 $a Cornell University. $3 530586
773 0 $t Dissertation Abstracts International $g 68-08B.
790 $a 0058
790 1 0 $a Shanmugasundaram, Jayavel, $e advisor
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3276833