Semantic Data Integration Methods for Chemical Domain

There is a huge amount of chemical data in the Web. Collecting those data and realizing the integration of their structured and semantic[1] data are one of the important issues in chemical domain. Traditional search engines in chemical domain provide some basic functionalities such as ranking with the support of some simple queries, Search results returned by those traditional search engines need to be improved, so that it can provide more accurate data. In order to achieve these goals, we develop several methods for the integration of semantic[10] data for the chemical domain[2]. In this paper, we explore how to generate chemical semantic data/knowledge. We investigate how the integration of chemical semantic data can be achieved. We propose three different methods of data integration for big data in chemical domain. Those three methods are (i) name matching integration (ii) identification and integration by CAS number.( iii) integration by SMILES expressions. Through experimental analysis, we have obtained the corresponding precision rate and recall rate. We make an evaluation of those three integration methods in chemical domain.