A comparison of distance methods effectiveness in retrieving relevant articles in agricultural domain

The large volume of online and offline information that is available today has overwhelmed users' efficiency and effectiveness in processing this information in order to extract relevant information. The exponential growth of the volume of internet information complicates the process of accessing and retrieving relevant information. Thus, it is a very time consuming and complex task for user in accessing relevant information. Information retrieval (IR) is a branch of artificial intelligence that tackles the problem of accessing and retrieving relevant information. The aim of IR is to enable the available data source to be queried for relevant information efficiently and effectively. However, in retrieving relevant information, several methods have been proposed to measure the similarity between the posted query and the articles retrieved. Different distance methods will rank these articles differently. This paper studies and compares the effectiveness of using different distance methods in retrieving relevant documents based on 17 specific queries in the agricultural domain. The obtained results of the experiment are empirically evaluated.