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

Rayner Alfred, and Kim, Soon Gan and Kim , On Chin and Patricia Anthony, (2014) A comparison of distance methods effectiveness in retrieving relevant articles in agricultural domain. In: International Conference on Computational Science and Technology.

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Official URL: Http://dx.doi.org/10.1109/ICCST.2014.7045202

Abstract

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.

Item Type:Conference Paper (UNSPECIFIED)
Uncontrolled Keywords:Information Retrieval, Similarities Measurment, Euclidean Distance, Jaccard Extend Coefficient
Subjects:Q Science > QA Mathematics
ID Code:12239
Deposited By:IR Admin
Deposited On:12 Nov 2015 15:56
Last Modified:12 Nov 2015 15:56

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