PPT-Distance and Similarity Measures

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. energies. D.A. . Artemenkov. , G.I. . . Lykasov. , . A.I. . . Malakhov. Joint Institute for Nuclear Research. malakhov@lhe.jinr.ru. Hadron Structure 2015, June 29 – July 3, 2015, . Horn. ý. . . 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,. -. based Clustering. Mohammad. . Rezaei. , Pasi Fränti. rezaei@cs.uef.fi. Speech. and . Image. . Processing. . Unit. University of Eastern Finland. . August 2014. Keyword-Based Clustering. An object such as a text document, website, movie and service can be described by a set of keywords. CMPS 561-FALL 2014. SUMI SINGH. SXS5729. Protein Structure . 2. RPDFCLEPPYAGACRARIIRYFYNAKAGLCQ. Primary Structure. Sequence of Amino Acids. . Not . enough for functional prediction.. Tertiary Structure. Ciro . Cattuto. , Dominik Benz, Andreas . Hotho. , . Gerd. . Stumme. Presented by. Smitashree. . Choudhury. Overview. Motivation. Measures of . semantic Relatedness. Semantic . Grounding of measures. these theories have explanatory power domains partially role of relational judgments. Previous structural and aspects of notion of relational similarity by the fact that and her some ways there is in 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) . Warm Up. 1.. . If . ∆. QRS.  . ∆. ZYX. , identify the pairs of congruent angles and the pairs of congruent sides.. Solve each proportion.. 2.. . 3.. . . x . = 9. x . = 18. . Q. Word . Similarity: . Distributional Similarity (I). Problems with thesaurus-based . meaning. We don’t have a thesaurus for every language. Even if we do, . they have problems with . recall. M. any . 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». Jing . Zhang, . Jie. . Tang . , Cong . Ma . , . Hanghang. . Tong . , Yu . Jing . , and . Juanzi. . Li. Presented by Moumita Chanda Das . Outline. Introduction. Problem formulation. Panther using path sampling. 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. Warm Up. Solve each proportion.. 1.. . . 2.. . 3.. 4. . If . ∆. QRS . ~ . ∆. XYZ. , identify the pairs of congruent angles and write 3 proportions using pairs of corresponding sides.. . Text Similarity. Motivation. People can express the same concept (or related concepts) in many different ways. For example, “the plane leaves at 12pm” vs “the flight departs at noon”. Text similarity is a key component of Natural Language Processing.