PPT-String Similarity

Author : conchita-marotz | Published Date : 2017-09-04

CSE HKUST March 20 Recap String declaration str1Hong str2Kong String Operators strr str1str2 H in strr String Slicing strr i strr i strr i

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String Similarity: Transcript


CSE HKUST March 20 Recap String declaration str1Hong str2Kong String Operators strr str1str2 H in strr String Slicing strr i strr i strr i . 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’. Corpora and Statistical Methods. Lecture 6. Semantic similarity. Part 1. Synonymy. Different phonological. /orthographic. words. highly related meanings. :. sofa / couch. boy / lad. Traditional definition:. from . GOMMA. Michael . Hartung. , Lars Kolb, . Anika. . Groß. , Erhard Rahm. Database . Research Group. University of . Leipzig. 9th . Intl. . . Conf. . on Data Integration. in . the. Life . Sciences. 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 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. 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». a Multi-Layered Indexing Approach. Yongjiang Liang, . Peixiang Zhao. CS @ FSU. zhao@cs.fsu.edu. Outline. Introduction. State-of-the-art solutions. ML-Index & similarity search. Experiments. Conclusion. of Binaries. Yaniv David. , Nimrod . Partush. , . Eran. . Yahav. . @. *. The research leading to these results has received funding . from the . European Union's - Seventh Framework . Programme. (FP7) under grant agreement n° . CS159 . Fall . 2014. Admin. Assignment 4. Quiz #2 Thursday. Same . rules as quiz #1. First 30 minutes of class. Open book and . notes. Assignment 5 out on Thursday. Quiz #2. Topics. Linguistics 101. Parsing. 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.. . with Edit-Distance Constraints. Dong . Deng . (. Tsinghua, . Beijing, China. ). Guoliang. Li . (. Tsinghua, . Beijing, China. ). Jianhua. Feng. . (Tsinghua, Beijing, China). Wen-. Syan. Li(SAP Labs, Shanghai, China). 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. 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. 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.

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