Ontology Evolution Using Recoverable SQL Logs
Source of Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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.
Springer International Publishing
Bloom filter, DFS, Online transaction processing, Ontology evolution, RecSQL, SQL logs
Yousaf, Awais; Khattak, Asad Masood; and Khan, Kifayat Ullah, "Ontology Evolution Using Recoverable SQL Logs" (2021). All Works. 4419.
Indexed in Scopus