Test of Data Query in Thai Text between Text Processing according to Semantic Text Similarity Measurement with Genetic Algorithm and Access to Data using Structured Query Language
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Abstract
Data query system by keyword has been implemented in different fields such as query of frequently asked questions or answers by customer, query of information related to products or services, etc. Data query in various systems mostly use structured query language to access data. However, for data query in Thai text by structured query language, several issues are encountered including inappropriate information delivery, inaccurate information and deviated from user requirement. This article aims to present the test of data query in Thai text between text processing according to semantic text similarity measurement with genetic algorithm and access to data via structured query language as guidance of data query in Thai text using text processing according to semantic text similarity measurement with genetic algorithm that program developer is able to use as reference in data query development for higher efficiency.
This study is conducted based on mixed methods research comprising of qualitative research and quantitative research by applying document research methods and experimental research by developing test program for data query in Thai text using text processing according to semantic text similarity measurement with genetic algorithm as well as test program for data access by structured query language. The two programs were tested in order to compare the performance using 2 testing criteria including queried text discovery rate and data query processing time. Data query test was conducted for 25 rounds and 99 experimental texts were used. Also, the same search term was used in the performance test of both programs.
The study indicated that data query in Thai text using text processing according to semantic text similarity measurement with genetic algorithm has higher efficiency than access to data via structured query language with statistic t value equal to 159.716 (p<0.01) for average text discovery rate with statistical significance of 0.01 and statistic t value equal to -16.237 (p<0.01) for data query processing time with statistical significance of 0.01.
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