Search results
Results from the WOW.Com Content Network
In linguistics, lexical similarity is a measure of the degree to which the word sets of two given languages are similar. A lexical similarity of 1 (or 100%) would mean a total overlap between vocabularies, whereas 0 means there are no common words. There are different ways to define the lexical similarity and the results vary accordingly.
The metrics compare an automatically produced summary or translation against a reference or a set of references (human-produced) summary or translation. ROUGE metrics range between 0 and 1, with higher scores indicating higher similarity between the automatically produced summary and the reference.
BLEU (bilingual evaluation understudy) is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Quality is considered to be the correspondence between a machine's output and that of a human: "the closer a machine translation is to a professional human translation, the better it is" – this is the central idea behind BLEU.
Software suite to search and cluster huge sequence sets. Similar sensitivity to BLAST and PSI-BLAST but orders of magnitude faster: Protein: Steinegger M, Mirdita M, Galiez C, Söding J [10] 2017 USEARCH Ultra-fast sequence analysis tool: Both: Edgar, R. C. (2010). "Search and clustering orders of magnitude faster than BLAST". Bioinformatics.
Scores for each position are obtained frequencies of substitutions in blocks of local alignments of protein sequences. [7] BLOSUM r The matrix built from blocks with less than r% of similarity E.g., BLOSUM62 is the matrix built using sequences with less than 62% similarity (sequences with ≥ 62% identity were clustered together).
The higher the Jaro–Winkler distance for two strings is, the less similar the strings are. The score is normalized such that 0 means an exact match and 1 means there is no similarity. The original paper actually defined the metric in terms of similarity, so the distance is defined as the inversion of that value (distance = 1 − similarity).
Calculate a similarity score that is the sum of the joined regions penalising for each gap 20 points. This initial similarity score ( initn ) is used to rank the library sequences. The score of the single best initial region found in step 2 is reported ( init1 ).
SimRank is a general similarity measure, based on a simple and intuitive graph-theoretic model.SimRank is applicable in any domain with object-to-object relationships, that measures similarity of the structural context in which objects occur, based on their relationships with other objects.