'Value pairs' diaporamas de présentation

Cloud Computing Systems

Cloud Computing Systems. Lin Gu. Hong Kong University of Science and Technology. Sept. 14, 2011. How to effectively compute in a datacenter?. Is MapReduce the best answer to computation in the cloud? What is the limitation of MapReduce?

758 views • 62 slides

Issues with Web Search Engines SI650: Information Retrieva l

Issues with Web Search Engines SI650: Information Retrieva l. Winter 2010 School of Information University of Michigan. A Typical IR System Architecture. docs. INDEXING. Query Rep. Doc Rep. query. User. Ranking. SEARCHING. results. INTERFACE. Feedback. judgments.

538 views • 44 slides

CS378 - Mobile Computing

CS378 - Mobile Computing. Intents. Intents. Allow us to use applications and components that are part of Android System start activities start services deliver broadcasts and allow other applications to use the components of the applications we create

501 views • 38 slides

Microdata for Dallas County Historical & Genealogical Cemetery Data

Microdata for Dallas County Historical & Genealogical Cemetery Data. Tony Hanson Webmaster. Presentation & Related Info. http://dallasgenealogy.org/DigitalFrontiers. What You Will Learn. What is Microdata How Microdata is used Why Microdata is significant. The Problem.

458 views • 35 slides

CSCI 2720

CSCI 2720. Hashing Spring 2005. Hashing. Motivation Techniques Hash functions. Implementing Dynamic Dictionaries. Want a data structure in which finds/searches are very fast As close to O(1) as possible minimum number of executed instructions per method

644 views • 30 slides

Decision Trees

Decision Trees. Example. Example 2. Examples, which one is better?. Good when. Samples are attribute-value pairs Target function has discrete output values Disjunctions required Missing, noisy training data. Construction. Top down construction

418 views • 29 slides

Using Hadoop & HBase to build content relevance & personalization

385 views • 27 slides

MapReduce

MapReduce. Outline. Purpose Example Method Advanced. purpose. Purpose. Data mining Data processing. example. Example. Find the maximum temperature of year National Climatic Data Center(NCDC) The data is stored using a line-oriented ASCII format , in which each line is a record

412 views • 25 slides

OOPs

OOPs. Object oriented programming. Abstract data types. Representationof type and operations in a single unit Available for other units to create variables of the type Possibility of hiding data structure of type and implementation of operations. Limitations of ADT and OOP extensions.

537 views • 21 slides

Mining Functional Dependencies from Data

Mining Functional Dependencies from Data. Hong Yao and Howard J. Hamilton Presented By Stephen Lynn. Rule Mining. Algorithmic process that takes data as input and yields rules such as: Association Rules Implications Functional dependencies. Overview. Goals/Objectives

331 views • 18 slides

COMPSCI 107 Computer Science Fundamentals

263 views • 16 slides

MapReduce : Simplified Data Processing on Large Clusters

MapReduce : Simplified Data Processing on Large Clusters. Appendix A: Word Frequency Alex Newton Billy Coss. Contents. Abstract Introduction MapReduce Word Frequency Analysis Sample Code. Abstract. MapReduce is a model used to analyze large amounts of data

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WDD Lecture 4

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Simple Canvas Example

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Dictionaries

188 views • 6 slides

Quality-of-Information Aware Transmission Policies with Time-Varying Links Ertugrul N . Ciftcioglu and Aylin Yener

. . . . Motivation. QoI vs QoS: QoI : associated with a piece of information can be defined as the value provided by it to the end user/application application dependent different from the notion of Quality of Service (QoS)

142 views • 1 slides