A fuzzy similarity measure for search results evaluation

The wide spread of the world wide web, the accelerating internet technologies development and the continuous upload of documents has produced large volumes of data. As a result, a huge amount of similar information is available on the web however very difficult to retrieve the best, concise and most precise one. In addition, the continuous upload of information leads to another issue which is documents' redundancy. It still an issue that irritates researchers due to the multiplicity of duplicated documents. Hence, the unsatisfaction of the user is due to the irrelevance and the multiple duplications in the search results. Therefore, the need to study the fields of information retrieval and document similarity is essential to ameliorate the results. Working on retrieving and comparing information, then deleting duplications will finally achieve the needed results in short time and efficient way. For this reason, we propose, in this paper, a new approach which detects and deletes automatically duplicated research results. This approach is based on fuzzy logic and distance measurements. In fact, it has shown promising results.