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We discuss the size-bias inherent in several chemical similarity coefficients when used for the similarity searching or diversity selection of compound collections. Limits to the upper bounds of 14 standard similarity coefficients are investigated, and the results are used to identify some exceptional characteristics of a few of the coefficients. An(More)
This report explains our plagiarism detection method using fuzzy semantic-based string similarity approach. The algorithm was developed through four main stages. First is pre-processing which includes tokenisation, stemming and stop words removing. Second is retrieving a list of candidate documents for each suspicious document using shingling and Jaccard(More)
The features are considered the cornerstone of text summarization. The most important issue is what feature to be considered in a text summarization process. Including all the features in the summarization process may not be considered as an optimal solution. Therefore, other methods need to be deployed. In this paper, random five features used and(More)
Many different types of similarity coefficients have been described in the literature. Since different coefficients take into account different characteristics when assessing the degree of similarity between molecules, it is reasonable to combine them to further optimize the measures of similarity between molecules. This paper describes experiments in which(More)
—Text summarization can be classified into two approaches: extraction and abstraction. This paper focuses on extraction approach. The goal of text summarization based on extraction approach is sentence selection. One of the methods to obtain the suitable sentences is to assign some numerical measure of a sentence for the summary called sentence weighting(More)
Many of the conventional similarity methods assume that molecular fragments that do not relate to biological activity carry the same weight as the important ones. One possible approach to this problem is to use the Bayesian inference network (BIN), which models molecules and reference structures as probabilistic inference networks. The relationships between(More)