Supporting Schema References in Keyword Queries Over Relational Databases

Relational Keyword Search (R-KwS) systems enable naive/informal users to explore and retrieve information from relational databases without knowing schema details or query languages. They take a keyword query, locate their corresponding elements in the target database, and connect them using information on PK/FK constraints. Although there are many such systems in the literature, most of them only support queries with keywords referring to the contents of the database and just very few support queries with keywords refering the database schema. We propose Lathe, a novel R-KwS that supports such queries. To this end, we first generalize the well-known concepts of Candidate Joining Networks (CJNs) and Query Matches (QMs) to handle keywords referring to schema elements and propose new algorithms to generate them. Then, we introduce two major innovations: a ranking algorithm for selecting better QMs, yielding the generation of fewer but better CJNs, and an eager evaluation strategy for pruning void useless CJNs. We present experiments performed with query sets and datasets previously experimented with state-of-theart R-KwS systems. Our results indicate that Lathe can handle a wider variety of queries while remaining highly effective, even for databases with intricate schemas.

Automated summary

R-KwS systems allow naive/informal users to explore and retrieve information from relational databases without knowing schema details or query languages. Lathe is a novel R-KwS system that supports keyword queries referring to the database schema, and it improves query effectiveness through a ranking algorithm and evaluation strategy.