PPT-Distance and Similarity Measures

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Bamshad Mobasher DePaul University Distance or Similarity Measures Many data mining and analytics tasks involve the comparison of objects and determining their

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Distance and Similarity Measures: Transcript

Bamshad Mobasher DePaul University Distance or Similarity Measures Many data mining and analytics tasks involve the comparison of objects and determining their similarities or dissimilarities. Presented by:. Akshay. Kumar. Pankaj. . Prateek. Are these similar?. Number ‘1’ vs. color ‘red’. Number ‘1’ vs. ‘small’. Horse vs. Rider. True vs. false . ‘. Monalisa. ’ vs. ‘Virgin of the rocks’. Input for Multidimensional Scaling and Clustering. Distances and Similarities. Both are ways of measuring how similar two objects are. Distances increase as objects are less similar. The distance of an object to itself is 0. Corpora and Statistical Methods. Lecture 6. Semantic similarity. Part 1. Synonymy. Different phonological. /orthographic. words. highly related meanings. :. sofa / couch. boy / lad. Traditional definition:. Ciro . Cattuto. , Dominik Benz, Andreas . Hotho. , . Gerd. . Stumme. Presented by. Smitashree. . Choudhury. Overview. Motivation. Measures of . semantic Relatedness. Semantic . Grounding of measures. Pattern Recognition . 2015/2016. Marc van Kreveld. Measures in mathematics. Functions from “subsets” to the reals. A . measure. obeys the properties:. Non-. negativeness. : for any subset X, f(X) . Case-based reasoning. Introduction. Common term in everyday language, where two objects usually are considered similar if they look or sound similar. Similarity is a core concept within CBR. From a CBR perspective: «Two problems are similar if they have similar solutions». CSE, HKUST. March 20. Recap. String declaration. str1=“Hong”. str2=“Kong”. String Operators. strr. =str1+str2. “H” in . strr. String Slicing. strr. [. i. ]. strr. [:. i. ]. strr. [. i. :]. June 8. th. , 2017. International Conference on Multimedia Retrieval. ICMR 2017. Bucharest, Romania. Yash Garg. CIDSE, Arizona State. University. Tempe, USA 85281. ygarg@asu.edu. Silvestro Roberto Poccia. Centrality. , Similarity, and . Influence. Edith Cohen . Tel Aviv University. Graph Datasets:. Represent relations between “things”. Bowtie structure of the Web . Broder. et. al. 2001. Dolphin interactions. Bamshad Mobasher. DePaul University. Distance or Similarity Measures. Many data mining and analytics tasks involve the comparison of objects and determining in terms of their similarities (or dissimilarities). Presenter. : Monica Farkash. Bryan Hickerson. . mfarkash@us.ibm.com. . bhickers@us.ibm.com. . 2. Outline. The challenge: Providing a subset from a regression test suite. Our new Jaccard/K-means (JK) approach . Function approximation does not work: . F(x): x->y, x feature vector, y: label, but we don’t know y yet. Patterns may still exist (depending on the relationship between records). What is clustering. Financial Services. Dhagash. Mehta. BlackRock, Inc.. Disclaimer: The views expresses here are those of the authors alone and not of BlackRock, Inc.. Introduction: Similarity. Scene from Alice’s Adventures in Wonderland by Lewis Carroll, 1865. Artist: John Tenniel. Sketching, Locality Sensitive Hashing. SIMILARITY AND DISTANCE. Thanks to:. Tan, Steinbach, . and Kumar, “Introduction to Data Mining”. Rajaraman. . and . Ullman, “Mining Massive Datasets”. Similarity and Distance.

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