Sentence examples for methods for similarity from inspiring English sources

The paper surveys the existing mathematical methods for similarity measurements and extends them to cope with different data formats.

At the time, there were mainly two methods for similarity analysis: the fingerprint description approach [4, 6] and the inductive logic programming approach [7 9].

Compared with the existing methods for similarity analysis, the examination of similarities/dissimilarities illustrates that the proposed method with the computational complexity of O(N) is effective for these three kinds of biological sequences, and bears the universality for them.

Several indexing methods for similarity searches in graph databases exist.

However, these methods for similarity calculation are only at a word or concept level rather than a semantic level, since they measure the similarity merely based on the common words or concepts in the query and sentence, which is the major difficulty that limits the performance improvement for text summarization system.

Accordingly, we established a housekeeping RNA database (see Methods) for similarity-based elimination and obtained 8715 putative long non-coding transcripts after removing housekeeping RNAs (Fig.  1).

Among them, there are methods for similarities calculation, which are used by many bioinformatics applications.

We also apply an improved OEDTW method for similarity matching.

Hence, the paper experiments with a clustering method for similarity measurement of workflows called spectral clustering.

PSNR uses a pixel-based method for similarity evaluation, usually measured in decibels; thus a higher PSNR means higher similarity.

Maurya et al. [31] also proposed an interval-halving method for trend extraction and a fuzzy matching based method for similarity estimation and inferences.