Welcome to the InfoSci Platform
BDD-Based Combinatorial Keyword Query Processing under a Taxonomy Model

BDD-Based Combinatorial Keyword Query Processing under a Taxonomy Model

Shin-ichi Minato, Nicolas Spyratos
Copyright: © 2012 |Volume: 3 |Issue: 4 |Pages: 11
ISSN: 1947-9344|EISSN: 1947-9352|EISBN13: 9781466613881|DOI: 10.4018/ijoci.2012100104
Cite Article Cite Article

MLA

Minato, Shin-ichi, and Nicolas Spyratos. "BDD-Based Combinatorial Keyword Query Processing under a Taxonomy Model." IJOCI vol.3, no.4 2012: pp.52-62. http://doi.org/10.4018/ijoci.2012100104

APA

Minato, S. & Spyratos, N. (2012). BDD-Based Combinatorial Keyword Query Processing under a Taxonomy Model. International Journal of Organizational and Collective Intelligence (IJOCI), 3(4), 52-62. http://doi.org/10.4018/ijoci.2012100104

Chicago

Minato, Shin-ichi, and Nicolas Spyratos. "BDD-Based Combinatorial Keyword Query Processing under a Taxonomy Model," International Journal of Organizational and Collective Intelligence (IJOCI) 3, no.4: 52-62. http://doi.org/10.4018/ijoci.2012100104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Digital libraries are one of the key systems for an IT society, and supporting easy access to them is an important technical issue between a human and an intelligent system. Here the authors consider a publish/subscribe system for digital libraries which continuously evaluates queries over a large repository containing document descriptions. The subscriptions, the query expressions and the document descriptions, all rely on a taxonomy that is a hierarchically organized set of keywords, or terms. The digital library supports insertion, update and removal of a document. Each of these operations is seen as an event that must be notified only to those users whose subscriptions match the document's description. In this chapter, the authors present a novel method of processing such keyword queries. Their method is based on Binary Decision Diagram (BDD), an efficient data structure for manipulating large-scale Boolean functions. The authors compile the given keyword queries into a BDD under a taxonomy model. The number of possible keyword sets can be exponentially large, but the compiled BDD gives a compact representation, and enabling a highly efficient matching process. In addition, the authors' method can deal with any Boolean combination of keywords from the taxonomy, while the previous result considered only a conjunctive keyword set. In this chapter, they describe the basic idea of their new method, and then the authors show their preliminary experimental result applying to a document set with large-scale keyword domain under a real-life taxonomy structure.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.