Semantic Matching Based Automatic Meta-Search Engine

In this project, a semantic matching-based automatic meta-search engine will be developed. Meta-search engines send the user query to many search engines simultaneously, combining the results from the search engines. The presented results for the user should be combined into a list.The meta-search engine to be developed in this project will first select horizontal and vertical search engines and organize the user query for each search engine. For example, the syntax of the logical operators, the writing rules of statements, and the settings for each search engine will be organized.

The rank values of results from different search engines will be recalculated based on the calculated value from the user. Here, the results of the different methods currently used and the methods to be developed in this project will be extensively compared. Some of the current methods are: direct global-local schema mapping; all local schemes matching with automatic global element matching; domain knowledge-based scheme matching; bag of words; and latent semantic analysis. Especially the first 10 results from different search engines will be examined and used mainly in the list of results.

The most important innovative aspect of this project is that the same results from different search engines with different data fields will be combined automatically using semantic matching. Here, the words that have the same meaning in different areas of the same Web page and on different Web pages will be merged semantically. Combining the results from different search engines is the most important problem for metasearch engines. The main goal of this project is to develop new methods for combining the results from different search engines and obtaining better results compared with existing methods.