Mapping query terms to data and schema using content based similarity search in clinical information systems

This paper reports on the issues in mapping the terms of a query to the field names of the schema of an Entity Relationship (ER) model or to the data part of the Entity Attribute Value (EAV) model using similarity based Top-K algorithm in clinical information system together with an extension of EAV mapping for medication names. In addition, the details of the mapping algorithm and the required pre-processing including NLP (Natural Language Processing) tasks to prepare resources for mapping are explained. The experimental results on an example clinical information system demonstrate more than 84 per cent of accuracy in mapping. The results will be integrated into our proposed Clinical Data Analytics Language (CliniDAL) to automate mapping process in CliniDAL.