PPT-Learning Discriminative Projections for Text Similarity Measures

Scott Wentau Yih Joint work with Kristina Toutanova John Platt Chris Meek Microsoft Research Crosslanguage Document Retrieval English Query Doc Spanish Document Set Web Search amp Advertising. Carl . Doersch. , . Abhinav. Gupta, Alexei A. . Efros. CMU . CMU. UCB. The need for mid-level representations. 6 billion images. 70 billion images. Agenda. Beyond Fixed . Keypoints. Beyond . Keypoints. Open discussion. Part Discovery from Partial Correspondence. [. Subhransu. . Maji. and Gregory . Shakhnarovich. , CVPR 2013]. K. eypoints. in diverse categories. 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). – . An assessment of past emission projections reported by Member States under EU air pollution and greenhouse gas legislation. . Martin . Adams, Melanie Sporer. . Air and Climate Change Programme . (. mis. )Usage and (. mis. )Interpretation?. Greg Ball. BSPS meeting 16 December 2013: Gregball@orangehome.co.uk. Projections and Planning. Planners mainly interested in change over time rather than future stock. Corpora and Statistical Methods. Lecture 6. Semantic similarity. Part 1. Synonymy. Different phonological. /orthographic. words. highly related meanings. :. sofa / couch. boy / lad. Traditional definition:. Yang Mu, Wei Ding. University of Massachusetts . Boston. 2013 IEEE International Conference on Data . Mining. , Dallas, . Texas, Dec. 7. PhD Forum. Classification. Distance learning. Feature selection. – . An assessment of past emission projections reported by Member States under EU air pollution and greenhouse gas legislation. . Martin . Adams, Melanie Sporer. . Air and Climate Change Programme . 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. :]. Presented by Sole. Chapters 1 - 5. Introduction. Artificial intelligence. Build . systems . that . incorporate . knowledge . about a . domain to . reason. . on the basis of this knowledge and solve problems . By . Chee. . Wai. Lee. Tutorial Outline. General Introduction. Instrumentation. Trace Generation. Support for TAU profiles. Performance Analysis. Dealing with Scalability and Data Volume. General Introduction. 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.