'Index terms' diaporamas de présentation

APA Lunch & Learn: 10 Things to Know About APA Databases

APA Lunch & Learn: 10 Things to Know About APA Databases. Michael Miyazaki mmiyazaki@apa.org Alison K. Cody, MSLIS acody@apa.org Documentation/Training Specialists. APA Countdown. 1. New Journals in PsycARTICLES. Forthcoming: Evolutionary Behavioral Sciences.

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INDEXES AND INDEXING

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Information Retrieval

Information Retrieval. CSE 8337 Spring 2003 Modeling Material for these slides obtained from: Modern Information Retrieval by Ricardo Baeza-Yates and Berthier Ribeiro-Neto http://www.sims.berkeley.edu/~hearst/irbook/

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Information Retrieval

Information Retrieval. CSE 8337 Spring 2005 Modeling Material for these slides obtained from: Modern Information Retrieval by Ricardo Baeza-Yates and Berthier Ribeiro-Neto http://www.sims.berkeley.edu/~hearst/irbook/

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CS590D: Data Mining Prof. Chris Clifton

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Introduction to Digital Libraries Information Retrieval

Introduction to Digital Libraries Information Retrieval. Performance of search. 3 major classes of measuring performance precision / recall TREC conference series, http://trec.nist.gov/ space / time see Esler & Nelson, JNCA for an example

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THE NEW NEXIS Jude Hayes, MLS LexisNexis jude.hayes@lexisnexis

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Language and Information

Language and Information. LIS 610 November 6, 2002 Nina Wacholder nina@scils.rutgers.edu. Agenda. Role of language in information science Current research: Human Computer Interaction with Electronic Indexes and Index Terms. Textual information.

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University of Palestine

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Introduction

Introduction. IR systems usually adopt index terms to process queries Index term: a keyword or group of selected words any word (more general) Stemming might be used: connect: connecting, connection, connections An inverted file is built for the chosen index terms. Introduction. Docs.

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CS 430 / INFO 430 Information Retrieval

CS 430 / INFO 430 Information Retrieval. Lecture 10 Probabilistic Information Retrieval. Course Administration. Assignment 1 You should have received results by email Assignment 2 Will be posted on Wednesday. Calculation of tf.idf.

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Text Preprocessing

Text Preprocessing. Aims to create a correct text representation, according to the adopted model. Step: Lexical analysis; Case folding, numbers; Stop-words elimination; Stemming; (other preprocessing procedures ...). Preprocessing step. S tru c tur e. Index terms. Full text.

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Social networking

Social networking. FOR HIGHER EDUCATION Brenda Kerr Instructional Technology Specialist Middle Tennessee State University. Can You Use Social Media Applications to Collaborate with Students?. Twitter Hash Tags + Saved Searches + Archive Share text, links, photos, video Delicious Bookmarks

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Internet Resources Discovery (IRD)

Internet Resources Discovery (IRD). IR Queries. IR Basic Concepts. In the classic models: each document is described/summarized by a set of representative keywords called index terms . index terms are mainly nouns , but could be all the distinct terms in a document.

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Indexing

Indexing. Overview Approaches to indexing Automatic indexing Information extraction. Overview. Indexing : the transformation of documents to searchable data structures. May be manual or automatic Creates basis for direct search,or for search through index files.

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What is the correct order of working steps ?

What is the correct order of working steps ?. Methods Results Figures Tables Introduction References Discussion Abstract. ?. Personal experience M atthias. Idea about story Write outline Decide journal Decide autor list Figures and Tables Introduction Results Discussion

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DITA for Beginners

DITA for Beginners. Outline. Why DITA? Modularity Information Typing Semantic Tagging Open Source Reuse What is DITA?. Why DITA. Modularity Information Typing Semantic Tagging Open Source Reuse. Modularity. Storing information in small self-contained modules/information structures

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QUICK GUIDE FOR NOVICE SEARCHERS

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