Information Retrieval Transfer Cycle Dania Bilal IS 530 Fall 2007.

Slides:



Advertisements
Similar presentations
Develop a search statement for searching a database? First, you need to understand what a database is and how it is compiled. Then, you can learn how to.
Advertisements

Chapter 5: Introduction to Information Retrieval
INFO624 - Week 2 Models of Information Retrieval Dr. Xia Lin Associate Professor College of Information Science and Technology Drexel University.
Multimedia Database Systems
UCLA : GSE&IS : Department of Information StudiesJF : 276lec1.ppt : 5/2/2015 : 1 I N F S I N F O R M A T I O N R E T R I E V A L S Y S T E M S Week.
IS530 Lesson 12 Boolean vs. Statistical Retrieval Systems.
Web- and Multimedia-based Information Systems. Assessment Presentation Programming Assignment.
Information Retrieval in Practice
Search Engines and Information Retrieval
T.Sharon - A.Frank 1 Internet Resources Discovery (IRD) Classic Information Retrieval (IR)
Basic IR: Queries Query is statement of user’s information need. Index is designed to map queries to likely to be relevant documents. Query type, content,
Search Strategies Online Search Techniques. Universal Search Techniques Precision- getting results that are relevant, “on topic.” Recall- getting all.
Intelligent Information Retrieval CS 336 –Lecture 2: Query Language Xiaoyan Li Spring 2006 Modified from Lisa Ballesteros’s slides.
© Tefko Saracevic, Rutgers University1 1.Discussion 2.Information retrieval (IR) model (the traditional models). 3. The review of the readings. Announcement.
Parametric search and zone weighting Lecture 6. Recap of lecture 4 Query expansion Index construction.
Information Retrieval Concerned with the: Representation of Storage of Organization of, and Access to Information items.
INFO 624 Week 3 Retrieval System Evaluation
INFORMATION RETRIEVAL WEEK 1 AND 2
Information retrieval Finding relevant data using irrelevant keys Example: database of photographic images sorted by number, date. DBMS: Well structured.
© Tefko Saracevic 1 Information retrieval (IR): traditional model 1.Why? Rationale for the module. Definition of IR 2.System & user components 3.Exact.
WHAT HAVE WE DONE SO FAR?  Weeks 1 – 8 : various components of an information retrieval system  Now – look at various examples of information retrieval.
Overview of Search Engines
International Atomic Energy Agency INIS Training Seminar Principles of Information Retrieval and Query Formulation 07 – 11 October 2013 Vienna, Austria.
Search Engines and Information Retrieval Chapter 1.
The Cognitive Perspective in Information Science Research Anthony Hughes Kristina Spurgin.
LIS 506 (Fall 2006) LIS 506 Information Technology Week 11: Digital Libraries & Institutional Repositories.
Modern Information Retrieval Computer engineering department Fall 2005.
Chapter 2 Architecture of a Search Engine. Search Engine Architecture n A software architecture consists of software components, the interfaces provided.
Web Searching Basics Dr. Dania Bilal IS 530 Fall 2009.
Thanks to Bill Arms, Marti Hearst Documents. Last time Size of information –Continues to grow IR an old field, goes back to the ‘40s IR iterative process.
Information Retrieval Evaluation and the Retrieval Process.
1 Information Retrieval Acknowledgements: Dr Mounia Lalmas (QMW) Dr Joemon Jose (Glasgow)
Keyword vs. Controlled Vocabulary Searching 12 Basic Skills for IQ.
Information in the Digital Environment Information Seeking Models Dr. Dania Bilal IS 530 Spring 2006.
Chapter 6: Information Retrieval and Web Search
Search Engines. Search Strategies Define the search topic(s) and break it down into its component parts What terms, words or phrases do you use to describe.
Search engines are used to for looking for documents. They compile their databases by employing "spiders" or "robots" to crawl through web space from.
Search Engine Architecture
IT-522: Web Databases And Information Retrieval By Dr. Syed Noman Hasany.
Information in the Digital Environment Information Seeking Models Dr. Dania Bilal IS 530 Spring 2005.
Concepts and phrases 2. checked out (on loan): ödünç verilmiş/kullanıcı üzerinde The circulation status of an item that has been charged to a borrower.
Indexes and Abstracts: Dissecting the Resource By M. Leedy.
Introduction to Information Retrieval Aj. Khuanlux MitsophonsiriCS.426 INFORMATION RETRIEVAL.
Basics of Information Retrieval and Query Formulation Bekele Negeri Duresa Nuclear Information Specialist.
Information Retrieval CSE 8337 Spring 2007 Introduction/Overview Some Material for these slides obtained from: Modern Information Retrieval by Ricardo.
Recuperação de Informação Cap. 01: Introdução 21 de Fevereiro de 1999 Berthier Ribeiro-Neto.
Information Retrieval
- University of North Texas - DSCI 5240 Fall Graduate Presentation - Option A Slides Modified From 2008 Jones and Bartlett Publishers, Inc. Version.
Characteristics of Information on the Web Dania Bilal IS 530 Spring 2006.
Chapter. 3: Retrieval Evaluation 1/2/2016Dr. Almetwally Mostafa 1.
Xiaoying Gao Computer Science Victoria University of Wellington COMP307 NLP 4 Information Retrieval.
SIMS 202, Marti Hearst Final Review Prof. Marti Hearst SIMS 202.
Characteristics of Information on the Web Dania Bilal IS 530 Spring 2005.
Information Retrieval in Practice
Search Engine Architecture
Modern Information Retrieval
Information Retrieval and Web Search
Search Engine Architecture
Information Retrieval and Web Search
Concept of a document Lesson 3.
Database & Record Structure
Web & Databases Dania Bilal IS 530 Fall 2006.
Information Retrieval
Thanks to Bill Arms, Marti Hearst
Evaluation of IR Performance
Introduction to Information Retrieval
Search Engine Architecture
The ultimate in data organization
Information Retrieval and Web Design
Recuperação de Informação
Presentation transcript:

Information Retrieval Transfer Cycle Dania Bilal IS 530 Fall 2007

Information Retrieval System A set of components that interact to provide feedback Comprised of interlinked entities  Agency that creates the databases  People  Documents

Interlinked Entities Agency Documents People

IR Information Transfer Inputs Processes Objectives of the System Outputs

The IR Cycle Documents are analyzed, translated, indexed, and stored. Documents are organized  Cataloging (description/representation of docs.)  Subject indexing

The IR Cycle Subject indexing a) Determination of subject content (conceptual analysis) b) Translation of content into language of the system (controlled vocabulary) c) Abstracting

The IR Cycle Language of the system (controlled vocabulary)  List of subject headings (Pre-coordinate)  Thesauri (Pre-coordinate)  Classification scheme

The IR Cycle Documents are represented by other entities  Author(s)  Date of publication  Language  Identifiers Entities may become access points

The IR Cycle Documents are stored after indexing Document representation is entered into the matching mechanism A file of document surrogates is established File becomes available for searching using a variety of entities/access points

The IR Cycle User Query  Analyzed for conceptual content  Translated into the language of the system (matched against controlled vocabulary and keywords)  Matched against document surrogates in the database

The IR Cycle Output  A set of records found and deemed relevant to a user query User judgment of retrieval

User Judgment Relevance to information need Relevance ranking by IR system Relevance vs. pertinence

Document-Based IRs Input, output, and matching mechanisms Selection of documents (done by indexers) Analysis of documents (done by indexers) Document organization and representation (done by indexers)

Document-Based IRs Analysis of user query (done by system) Match of user query with relevant documents Delivery of documents (output)

The IR Cycle

Information Seeking Process of finding information to fill a knowledge gap User requests  Known item searches  Unknown item searches  Subject searches

Discussion How does the IR transfer cycle in databases varies from the cycle in Web search engines?

Search Logic Overview Boolean logic Search parameters  Phrase  Proximity  Use of specific fields to search  Nesting