Answering Comparison in Indonesian Question Answering System with Database

Abstract

In this research, we build a question answering system that can answer comparative questions. Our system contains two components, question analysis and answer processing. In question analysis, we use information extraction method to extract entities, aspects, relations, and constants from the question. We also classify the question into five question types such as entity-mentioned, entity-other, entity-all, aspect, and yes/no. These processes in question analysis component are solved by machine learning technique. In answer processing component, we process the comparison by using word lists and rules. The result of comparison processing is used to find the answer by generating query to get relevant data from the database. The query generation process is performed by using rules based on the question type. After that, the data from database is also processed based on question type to generate the answer. Based on the experiment results, our proposed method for comparison question answering system is promising.