JOURNAL ARTICLE

Keyword search over relational tables and streams

Alexander MarkowetzYin YangDimitris Papadias

Year: 2009 Journal:   ACM Transactions on Database Systems Vol: 34 (3)Pages: 1-51   Publisher: Association for Computing Machinery

Abstract

Relational Keyword Search (R-KWS) provides an intuitive way to query relational data without requiring SQL, or knowledge of the underlying schema. In this article we describe a comprehensive framework for R-KWS covering snapshot queries on conventional tables and continuous queries on relational streams. Our contributions are summarized as follows: (i) We provide formal semantics, addressing the temporal validity and order of results, spanning uniformly over tables and streams; (ii) we investigate two general methodologies for query processing, graph based and operator based , that resolve several problems of previous approaches; and (iii) we develop a range of algorithms and optimizations covering both methodologies. We demonstrate the effectiveness of R-KWS, as well as the significant performance benefits of the proposed techniques, through extensive experiments with static and streaming datasets.

Keywords:
Computer science SQL Snapshot (computer storage) Relational database Schema (genetic algorithms) Data stream mining Information retrieval Data mining Theoretical computer science Database

Metrics

15
Cited By
3.09
FWCI (Field Weighted Citation Impact)
42
Refs
0.93
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Database Systems and Queries
Physical Sciences →  Computer Science →  Computer Networks and Communications
Data Management and Algorithms
Physical Sciences →  Computer Science →  Signal Processing
Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence
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