Ontology Evolution Using Recoverable SQL Logs

Document Type

Conference Proceeding

Source of Publication

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Publication Date

1-1-2021

Abstract

Logs of SQL queries are useful for building the system design, upgrading, and checking which SQL queries are running on certain applications. These SQL queries provide us useful information and knowledge about the system operations. The existing works use SQL query logs to find patterns when the underlying data and database schema is not available. For this purpose, a knowledge-base in the form of an ontology is created which is then mined for knowledge extraction. In this paper, we have proposed an approach to create and evolve an ontology from logs of SQL queries. Furthermore, when these SQL queries are transformed into the ontology, they loose their original form/shape i.e., we do not have original SQL queries. Therefore, we have further proposed a strategy to recover these SQL queries in their original form. Experiments on real world datasets demonstrate the effectiveness of the proposed approach.

ISBN

9783030763510

ISSN

0302-9743

Publisher

Springer International Publishing

Volume

12632 LNCS

First Page

509

Last Page

517

Disciplines

Computer Sciences

Keywords

Bloom filter, DFS, Online transaction processing, Ontology evolution, RecSQL, SQL logs

Scopus ID

85111401679

Indexed in Scopus

yes

Open Access

no

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