Similarity Scores

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Information Theoretic Similarity Measures for Inter-domain

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information theoretic similarity measures for inter-domain predicate mapping nikita i. lytkin dept. of computer science rutgers university [email protected] william m. pottenger dimacs rutgers university [email protected] abstract the development of similarity functions for firstorder logic predicates and argument types is the initial step in the development of techniques

A Melodic Similarity Measure Based on Human Similarity Judgments

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a melodic similarity measure based on human similarity judgments naresh n. vempala,*1 frank a. russo*2 *department of psychology, ryerson university, canada [email protected], [email protected] abstract music software applications often require similarity-finding methods. one instance involves performing content-based searches, where music similar to what is heard by the listener is retrieved

Similarity and self similarity in fluid dynamics

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fundamentals of cosmic physics editors v m. canula, nasa. institute for space studies, new york, ny 10025 bruce g. elmegreen, ibm, thomas j. watson research center, p.o. box 218, yorktown heights, ny 10598 associate editors c. ferro fontan, university of buenos aires, argentina john s. gallagher iii, lowell

Evolution of Semantic Similarity - A Survey

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arxiv:2004.13820v2 [cs.cl] 30 jan 2021 evolution of semantic similarity - a survey dhivya chandrasekaran and vijay mago, lakehead university estimating the semantic similarity between text data is one of the challenging and open research problems in the field of natural language processing (nlp). the versatility of natural language makes

FICO Credit-Based Insurance Scores

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fico® credit-based insurance scores 1. most consumers benefit from the use of insurance scores— lower premiums—in its july 2007 report, “credit-based insurance scores: impacts on consumers of automobile insurance,” the federal trade commission noted “if credit-based insurance scores are used, more consumers (59%) would be predicted to have a decrease

Reliability of Index and Subtest Discrepancy Scores from the

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western kentucky university topscholar® masters theses & specialist projects graduate school spring 2020 reliability of index and subtest discrepancy scores from the kabc-ii nu grant hacherl western kentucky university, [email protected] follow this and additional works at: https://digitalcommons.wku.edu/theses part of the cognition and perception commons, cognitive psychology

Scale Scores and Mean Scale Scores

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scale scores and mean scale scores what is a scale score? students earn a scale score on each colorado measures of academic success assessment they take. for english language arts, the scale scores range between 650 and 850 and for science the range is 300 to 900. performance levels

Recent Trends in Mean Scores and Characteristics of Test

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u.s. department of education recent trends in mean scores and characteristics of test-takers on praxis ii licensure tests recent trends in mean scores and characteristics of test-takers on praxis ii licensure tests prepared by: drew h. gitomer yi qi educational testing service (ets) principal investigator drew h. gitomer, ets

Generating Rubric Scores From Pairwise Comparisons

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generating rubric scores from pairwise comparisons shayne miel, david adamson, bronwyn woods ­ turnitin holly garner ­ evered abstract using pairwise comparisons, or comparative judgement scoring, to score essays on a holistic rubric is potentially a more reliable and less expensive scoring method than traditional handscoring. however, a challenge it

Accuracy of Clinical Risk Scores in Predicting Post-rtPA

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original article accuracy of clinical risk scores in predicting post-rtpa intracerebral hemorrhage in a thai cohort suengtaworn a, md¹, saposnik g, md, frcpc, msc², hurst cp, phd³, poungvarin n, md, mrcp, frcp, mmsc, frs(t)¹, nilanont y, md⁴ ¹ division of neurology, faculty of medicine siriraj hospital, mahidol university, bangkok,

The Effects of Similarity and Individual Differences on

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the effects of similarity and individual differences on comparison and transfer samuel day ([email protected]) dept. of brain & behavioral sciences, 1001 e. 10th st. bloomington, in 47405 usa robert l. goldstone ([email protected]) dept. of brain & behavioral sciences, 1001 e. 10th st. bloomington, in 47405 usa thomas

Similarity Learning for High Dimensional Sparse Data

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similarity learning for high dimensional sparse data kuan liu aurélien bellet fei sha motivation measuring distance or similarity is a key component of ai, machine learning, pattern recognition, data mining, etc ex: nearest neighbor classification, clustering, information retrieval. how to define good distances between objects? metric learning [1]: learn

Linear resolvent growth test for similarity of a weak

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ark. mat., 39 (2001), 95 119 @ 2001 by institut mittag-leffler. all rights reserved linear resolvent growth test for similarity of a weak contraction to a normal operator stanislav kupin a b s t r a c t . it is proved in benarnara-nikolski [1] that if the

Structured and Deep Similarity Matching via Structured and

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structured and deep similarity matching via structured and deep hebbian networks dina obeid hugo ramambason cengiz pehlevan john a. paulson school of engineering and applied sciences harvard university cambridge, ma, usa {[email protected],[email protected],[email protected]}.harvard.edu abstract synaptic plasticity is widely accepted to be the mechanism behind learning in the brain’s neural networks. a

Automatic Detection and Correction for Chinese Misspelled

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automatic detection and correction for chinese misspelled words using phonological and orthographic similarities tao-hsing chang department of computer science and information engineering, national kaohsiung university of applied sciences [email protected] hsueh-chih chen department of educational psychology and counseling national taiwan normal university [email protected] yuen-hsien tseng information technology center

Two Forces in the Development of Relational Similarity

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gentner, d., rattermann, m. j., markman, a. b., & kotovsky, l. (1995).two forces in the development of relational similarity. in t. j. simon & g. s. halford (eds.), developing cognitive competence: new approaches to process modeling (pp. 263-313). hillsdale, nj: lea. two forces in the development of relational similarity dedre

Fuzzy-Semantic Similarity for Automatic Multilingual

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(ijacsa) international journal of advanced computer science and applications, vol. 8, no. 9, 2017 fuzzy-semantic similarity for automatic multilingual plagiarism detection hanane ezzikouri lmacs laboratory, mathematics department, faculty of sciences and techniques, sultan moulay slimane university beni-mellal, bp: 523, morocco mohamed erritali tiad laboratory, computer sciences department, faculty

Semantic Similarity Measures as Tools for Exploring the Gene

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semantic similarity measures as tools for exploring the gene ontology p.w. lord, r.d. stevens, a. brass, c.a.goble pacific symposium on biocomputing 8:601-612(2003) semantic similarity measures as tools for exploring the gene ontology p.w.lorda, r.d. stevens, a. brass and c.a.goble department of computer science university of manchester oxford road manchester

Sibling similarity in family formation

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sibling similarity in family formation paper prepared for the annual meeting of the population association of america, 2014 anette fasang & marcel raab humboldt university berlin & berlin social science center (wzb) jani erola & aleksi karhula university of turku, finland abstract sibling studies have been widely used to analyze

Developer Manual for py-stringmatching 0.2

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developer manual for py-stringmatching 0.2.x the magellan development team july 10, 2016 package’s homepage: https://sites.google.com/site/anhaidgroup/projects/py stringmatching. 1 introduction py stringmatching is a python package that consists of a variety of string tokenizers (e.g., whitespace tokenizer, qgram tokenizer) and string similarity measures (e.g., edit distance, jaccard measure, tf/idf) [1]. the goal