PPT-Google Similarity Distance

Author : giovanna-bartolotta | Published Date : 2015-09-20

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

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Google Similarity Distance: Transcript

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. 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). 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. Probability. Introduction to Biostatistics and Bioinformatics. Sequence Alignment Concepts . This Lecture. Sequence Alignment. Stuart M. Brown, Ph.D.. Center for Health Informatics and Bioinformatics. Corpora and Statistical Methods. Lecture 6. Semantic similarity. Part 1. Synonymy. Different phonological. /orthographic. words. highly related meanings. :. sofa / couch. boy / lad. Traditional definition:. Theory and Applications. Danai Koutra (CMU). Tina Eliassi-Rad (Rutgers) . Christos Faloutsos (CMU). SDM 2014. , Friday April 25. th. 2014, Philadelphia, PA. Who we are. Danai Koutra, CMU. Node and graph similarity,. 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. :]. 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 . Quiz. Which pair of words exhibits the greatest similarity?. 1. Deer-elk. 2. Deer-horse. 3. Deer-mouse. 4. Deer-roof. Quiz Answer. Which pair of words exhibits the greatest similarity?. 1. Deer-elk. 2. Deer-horse. 1. Provide the tools and expertise to determine commuting distances and times for a population of students using google maps.. How far are students from campus?. 2. Showcase the power of APIs and R.. 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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