Providing a new method for web mining using fuzzy multi-criteria algorithm and clustering of web pages and similar data

Web mining refers to exploring and searching the web for the purpose of finding specific data and information. Web mining is a branch of data mining, and data mining is referred to as the discovery databases. Web mining operations should be performed in such a way that the best results are presented to the user as soon as possible. With the rapid increase of information in the web world, there is a need to improve the speed and reliability of web mining operations. Due to the wide variety of available information in the Web world, they always expect to see the best answers they are looking for at the beginning of the results. In many cases, the web pages are not found user-friendly. That is why the main motivation for the article is to provide a method that improves the results presented to the user. In this paper, a new fuzzy method is proposed to increase the accuracy of the search for related search items, which makes clustering the same pages and data, and, using theweight and preference of each of the homogeneity parameters, calculates the similarity of the data Sheets and pages. The proposed algorithm is simulated in the software environment and the results are compared with the new algorithm presented

کلیدواژه ها:

Web mining ، data mining ، web clustering ، page similarity