A Query Evaluation Approach using Opinions of Turkish Financial Market Professionals

People who do not have expertise in the financial area may not see the relationship between the numerical and linguistic data. In our study, a knowledge discovery approach using Turkish natural language processing is recommended in order to respond to meaningful queries and classify them with high accuracy. Query corpus consists of randomly selected unique keywords. Quantitative evaluation is done in order to measure the classification performance. Experimental results indicate that our proposed approach is sufficiently consistent with and able to make categorical classifications correctly. The approach highlights the relationship between numerical and linguistic data obtained from Turkish financial market.