SUPPORTING KEYWORD SEARCH IN TEMPORAL DATABASES

Abstract

Keyword search over temporal databases provides an easy and convenient way for non-expert users, like financial analysts and clinicians, to query temporal databases without constructing complex SQL queries. Existing works do not consider the Object-Relationship-Attribute (ORA) semantics of temporal databases in database schema design and keyword query processing. As a result, the databases do not properly capture the temporal and non-temporal semantics in the real world, and query processing do not evaluate the possible query interpretations involving time conditions. Further, current temporal keyword search approaches do not support negation, aggregates and GROUPBY, which limits the expressness of keyword queries. This thesis overcomes the above problems by adopting a semantic approach to design temporal database schema and process temporal keyword query. The proposed temporal keyword query supports ordinary keywords, aggregates, group-by, negation and time condition.