Interpretation of natural language queries for effective data exploration over heterogeneous databases: applications to biomedical domain

Abstract

Data exploration is an essential process for discovering novel knowledge in scientific researches. However, it is difficult for field experts to find out the target data only by exploration, especially when the data are scattered over multiple and heterogeneous databases. Since such data are usually associated with one another, there may be appropriate sequences of searches that the field experts can use for queries to reach the target data. In order to help such data exploration, conventional database interfaces provide useful tools for querying in keywords or structured forms. However, we argue that they are inadequate to express the queries for sequences of searches in multiple databases which embody diverse relations among their data. In order to describe such queries in a convenient and expressive manner, we propose to use natural language queries (NLQs) to interact with the databases. Such a database interface shall automatically interpret NLQs into formal language queries (FLQs) that are in turn composed of small FLQs for different databases. This task requires us to address the problem of database heterogeneity due to the differences in formal query languages, database structures, and data contents. The dissertation addresses this problem by considering NLQs as terms and syntactic relations, which respectively correspond to data objects and their operations. We utilize SQL-like expressions to coordinate such terms and syntactic relations, resulting in FLQs via a straightforward mapping process. In this work, we present a method that derives the SQL-like expressions from NLQs in a Combinatory Categorial Grammar (CCG) framework, and then translates the expressions into the locations of data objects accessible from our target databases. The method then constructs FLQs for such locations in possible sequences with accounts for data associations. Our method thus provides a fully automated way to locate and retrieve available data from databases. We also...