Shortest paths in graphs Based on slides by David Kauchak Shortest paths What is the shortest path from a to d? BD A CE Shortest paths BFS BD A CE Shortest paths What is the shortest path from a to d? B2D 3 3 1 CE 4 A 1 2 Shortest paths We can still […]
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CIS 455/555: Internet and Web Systems RPCs November 4, 2020 © 2020 A. Haeberlen, Z. Ives, V. Liu University of Pennsylvania 1 Plan for today n MapReduce n Example tasks n Hadoop and HDFS n Architecture n Using Hadoop n Using HDFS n Beyond MapReduce n Remote Procedure Calls n Web Services © 2020 A.
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T ee Baed ide b Ha Zh Read Seci 12, 13, 6, 18, 16.3 1 2 Trees Li e ae & e chid (a ) Tee e ae & e e chide Gah e e ae ad e e chide. Tee (ah defiii): ceced accic gah Tee (idcie
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Draft of April 1, 2009 Online edition (c) 2009 Cambridge UP An Introduction to Information Retrieval Online edition (c) 2009 Cambridge UP Cambridge University Press Cambridge, England Online edition (c) 2009 Cambridge UP An Introduction to Information Retrieval Christopher D. Manning Prabhakar Raghavan Hinrich Schütze DRAFT! DO NOT DISTRIBUTE WITHOUT PRIOR PERMISSION © 2009 Cambridge
Divide and conquer algorithms + Associated recurrences Sept. 3, 2020 Exc-ewplet I23 find selection e x it; else 4 max-_ a -43; iced- max =L; liel tor) if(aTi3>max) f (a -4. – exchange a ⇐ – n’s) ; a -Ln3 ; y= – sort SELECT CaEl. -n-is) (ALT. – B) sort (res) if for if
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SUMMATIVE 3 Requirements – All questions are worth 35 marks, except for the last question, which is worth 30 marks. – The first part is on monads and a game of chance. The second part is about parsing English. – Copy the file Summative3-Template.hs to a new file called Summative3.hs and write your solutions in
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COSC 336 Data Structures and Algorithms Mathematical tools for the analysis of algorithms Professor: Marius Zimand 1 Important functions The functions that appear commonly in the analysis of algorithms are: logarithms, polyno- mials, exponential, factorial. 1.1 Polynomials. A polynomial function is a function of the type p(n)=aknk +ak1nk1 +…+a1n+a0, where the coecients ak , .
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Abstract The Anatomy of a Large-Scale Hypertextual Web Search Engine Sergey Brin and Lawrence Page Computer Science Department, Stanford University, Stanford, CA 94305, USA sergey@cs.stanford.edu and page@cs.stanford.edu In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl
Motivation EE5806: Topics in Digital Image Processing Lecture Notes: Landmark registration • Wish to compare source image with target image (Fig. 1). • Need to align (i.e., register) source with target before comparison. Approach • We will deal with cases where the source image is a rotated, translated and scaled version of the target. Therefore,
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September 26, 2001 Research SRC Report 173 High-Performance Web Crawling Marc Najork Allan Heydon Systems Research Center 130 Lytton Avenue Palo Alto, California 94301 http://www.research.compaq.com/SRC/ Compaq Systems Research Center SRC’s charter is to advance the state of the art in computer systems by doing basic and applied research in support of our company’s business objectives.