Univrsity Of Tehran Press Journal of Information Technology Management 2980-7972 10 4 2018 12 01 Estimating the Parameters for Linking Unstandardized References with the Matrix Comparator 12 26 72758 10.22059/jitm.2019.274871.2332 EN Awaad Al-Sarkhi University of Arkansas at Little Rock, USA. John R. Talburt Associate Professor, University of Arkansas at Little Rock, USA. Journal Article 2019 01 27 This paper discusses recent research on methods for estimating configuration parameters for the Matrix Comparator used for linking unstandardized or heterogeneously standardized references. The matrix comparator computes the aggregate similarity between the tokens (words) in a pair of references. The two most critical parameters for the matrix comparator for obtaining the best linking results are the value of the similarity threshold and the list of stop words to exclude from the comparison. Earlier research has shown that the standard deviation of the token frequency distribution is strongly predictive of how useful stop words will be in improving linking performance. The research results presented here demonstrate a method for using statistics from token frequency distribution to estimate the threshold value and stop word selection likely to give the best linking results. The model was made using linear regression and validated with independent datasets. https://jitm.ut.ac.ir/article_72758_72b897868e02c41658fb6caf9ff2f3a8.pdf