Proximity Search in Databases
Roy Goldman, Narayanan Shivakumar, Suresh Venkatasubramanian, Hector Garcia-Molina
Full Paper (PDF)

Abstract
An information retrieval (IR) engine can rank documents based on textual proximity of keywords within each document. In this paper we apply this notion to search across an entire database for objects that are "near" other relevant objects. Proximity search enables simple "focusing" queries basedon general relationships among objects, helpful for interactive query sessions. We view the database as a graph, with data in vertices (objects) andrelationships indicated by edges. Proximity is defined based on shortest paths between objects. We have implemented a prototype search engine that uses this model to enable keyword searches over databases, and we have found it very effective for quickly finding relevant information. Computing the distance between objects in a graph stored on disk can be very expensive. Hence, we show how to build compact indexes that allow us to quickly find the distance between objects at search time. Experiments show that our algorithms are efficient and scale well.

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BIBTEX

@inproceedings{DBLP:conf/vldb/GoldmanSVG98,
author = {Roy Goldman and
Narayanan Shivakumar and
Suresh Venkatasubramanian and
Hector Garcia-Molina},
editor = {Ashish Gupta and
Oded Shmueli and
Jennifer Widom},
title = {Proximity Search in Databases},
booktitle = {VLDB'98, Proceedings of 24rd International Conference on Very
Large Data Bases, August 24-27, 1998, New York City, New York,
USA},
publisher = {Morgan Kaufmann},
year = {1998},
isbn = {1-55860-566-5},
pages = {26-37},
crossref = {DBLP:conf/vldb/98},
bibsource = {DBLP, http://dblp.uni-trier.de}
}


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