SlideShare une entreprise Scribd logo
1  sur  9
“Basic Search Technique”

By,
Sarika Meher
INTRODUCTION
• The incredible growth in the amount of electronic
information that has become available in the last
few years has made the ability to search &
navigate these e-sources increasingly important.
More often than not researching topic now
includes using not only print sources, it also
requires accessing information via the internet
OPACS, CD-ROMS, & commercial databases such
as westlaw, Firstserach, & Lexis.
BASIC SEARCH TECHNIQUES
1. Keyword & Phrase search:
A search can be conducted by using a single search term or a phrase
comprising more than one term.
Keyword search:
e.g., “Library”
Phrase Search:
e.g., “library management”
2. Truncation Search:
Truncation allows a search to be conducted for all the different forms
of words having the same common roots.
A number of different options are available for truncation:
• Right truncation:
E.g. compute*
• Left truncation:
E.g. *hyl will retrieve words like methyl, ethyl etc.
• Internal truncation:
E.g. col*r will retrieve both the terms colour & color.
3. PROXIMITY SEARCH
Here it allows us to specify how close two or more words must
appear in order to register a match. It is of 3 types:
(a) Word proximity
(b) Sentence proximity
(c)Paragraph proximity
(a) WORD PROXIMITY: E.g. “content collection”/4
It retrieve content & collection in 4 word difference.
Ordered proximity:
E.g. “content collection”/4
Unordered proximity:
E.g. “content collection”@4
(b)Sentence Proximity:
A sentence proximity allow to search for term which must be in the
same sentence.
E.g. “Library management”/S (ORDERED)
“Library management”@S (UNORDERED)
These two word must be appear in the same sentence.

(c)PARAGRAPH PROXIMITY:
It allows to search which must be occurring in same paragraph.
E.g. “Library automation”/P (ORDERED)
“Library automation”@P (UNORDERED)
These are two words must appear in same paragraph in it’s retrieval.
4. BOOLEAN SEARCH:
Many search engine allow use of ‘AND’, ‘OR’ & ‘NOT’ to narrow or
broaden a request.
OPERATOR AND
E.g. Library AND Automation
The result will consist of documents that contain both words i.e. library &
automation.
OPERATOR OR
E.g. Library OR Automation
It retrieves maximum number of document because it retrieves document
having library, having automation or both library and automation.
OPERATOR NOT
E.g. Library AND Automation NOT India
It retrieves documents having the word “Library and Automation” but not
having the word “India”.
5. LIMITING SEARCH:
E.g. Document, published after 2000
E.g. Library Automation, pdf

E.g. Birds nest, Hindi language.

6. FIELD SEARCH:
 Title Search
 URL Search
 Link Search
 File type Search
THANK YOU

Contenu connexe

Tendances

Inverted files for text search engines
Inverted files for text search enginesInverted files for text search engines
Inverted files for text search engines
unyil96
 
Science database noodletools
Science database noodletoolsScience database noodletools
Science database noodletools
elliotel
 
Honors Writing Seminar - Surface
Honors Writing Seminar - SurfaceHonors Writing Seminar - Surface
Honors Writing Seminar - Surface
Jenny Donley
 
Honors Writing Seminar 2015
Honors Writing Seminar 2015Honors Writing Seminar 2015
Honors Writing Seminar 2015
Jenny Donley
 
Van Tilburgh Spring 2014
Van Tilburgh Spring 2014Van Tilburgh Spring 2014
Van Tilburgh Spring 2014
Jenny Donley
 
Sherborn: Lyal - Digitising legacy taxonomic literature: processes, products ...
Sherborn: Lyal - Digitising legacy taxonomic literature: processes, products ...Sherborn: Lyal - Digitising legacy taxonomic literature: processes, products ...
Sherborn: Lyal - Digitising legacy taxonomic literature: processes, products ...
ICZN
 
Model of information retrieval (3)
Model  of information retrieval (3)Model  of information retrieval (3)
Model of information retrieval (3)
9866825059
 

Tendances (20)

Searching In SharePoint
Searching In SharePointSearching In SharePoint
Searching In SharePoint
 
20081009 meeting
20081009 meeting20081009 meeting
20081009 meeting
 
Inverted files for text search engines
Inverted files for text search enginesInverted files for text search engines
Inverted files for text search engines
 
Phrase Based Indexing
Phrase Based IndexingPhrase Based Indexing
Phrase Based Indexing
 
Science database noodletools
Science database noodletoolsScience database noodletools
Science database noodletools
 
Honors Writing Seminar - Surface
Honors Writing Seminar - SurfaceHonors Writing Seminar - Surface
Honors Writing Seminar - Surface
 
Honors Writing Seminar 2015
Honors Writing Seminar 2015Honors Writing Seminar 2015
Honors Writing Seminar 2015
 
LAWE2530
LAWE2530LAWE2530
LAWE2530
 
Nr 439 research database assignment form
Nr 439 research database assignment formNr 439 research database assignment form
Nr 439 research database assignment form
 
Nr 439 research database assignment form
Nr 439 research database assignment formNr 439 research database assignment form
Nr 439 research database assignment form
 
Linked data intro primer
Linked data intro primerLinked data intro primer
Linked data intro primer
 
Ehis Eds Europe May2009 Brussels Deel 1
Ehis Eds Europe May2009  Brussels   Deel 1Ehis Eds Europe May2009  Brussels   Deel 1
Ehis Eds Europe May2009 Brussels Deel 1
 
Van Tilburgh Spring 2014
Van Tilburgh Spring 2014Van Tilburgh Spring 2014
Van Tilburgh Spring 2014
 
Sherborn: Lyal - Digitising legacy taxonomic literature: processes, products ...
Sherborn: Lyal - Digitising legacy taxonomic literature: processes, products ...Sherborn: Lyal - Digitising legacy taxonomic literature: processes, products ...
Sherborn: Lyal - Digitising legacy taxonomic literature: processes, products ...
 
Indexing
IndexingIndexing
Indexing
 
LLB Dissertation Research Skills 2017
LLB Dissertation Research Skills 2017LLB Dissertation Research Skills 2017
LLB Dissertation Research Skills 2017
 
Model of information retrieval (3)
Model  of information retrieval (3)Model  of information retrieval (3)
Model of information retrieval (3)
 
Open Bibliography, Citations and Scholarship
Open Bibliography, Citations and ScholarshipOpen Bibliography, Citations and Scholarship
Open Bibliography, Citations and Scholarship
 
Data indexing presentation
Data indexing presentationData indexing presentation
Data indexing presentation
 
Basic Search Skills
Basic Search SkillsBasic Search Skills
Basic Search Skills
 

En vedette (6)

Sampling Techniqes
Sampling TechniqesSampling Techniqes
Sampling Techniqes
 
Library portal
Library portalLibrary portal
Library portal
 
Digital architecture
Digital architectureDigital architecture
Digital architecture
 
DIGITAL LIBRARY ARCHITECTURE
DIGITAL LIBRARY ARCHITECTUREDIGITAL LIBRARY ARCHITECTURE
DIGITAL LIBRARY ARCHITECTURE
 
MAPPING OF KNOWLEDGE IN COLON CLASSIFICATION
MAPPING OF KNOWLEDGE IN COLON CLASSIFICATION MAPPING OF KNOWLEDGE IN COLON CLASSIFICATION
MAPPING OF KNOWLEDGE IN COLON CLASSIFICATION
 
Colon Classification: An Overview
Colon Classification: An OverviewColon Classification: An Overview
Colon Classification: An Overview
 

Similaire à Meher ppt (1)

How to become an effective web searcher
How to become an effective web searcherHow to become an effective web searcher
How to become an effective web searcher
rangak
 
Honors English - Surface
Honors English - SurfaceHonors English - Surface
Honors English - Surface
Jenny Donley
 
Database Terms Concepts2
Database Terms  Concepts2Database Terms  Concepts2
Database Terms Concepts2
ejdmiller
 
Classics Information research skills for projects and dissertations
Classics Information research skills for projects and dissertationsClassics Information research skills for projects and dissertations
Classics Information research skills for projects and dissertations
Royal Holloway University of London
 
Chapter 1 Introduction to ISR (1).pdf
Chapter 1 Introduction to ISR (1).pdfChapter 1 Introduction to ISR (1).pdf
Chapter 1 Introduction to ISR (1).pdf
JemalNesre1
 
Being an independent & assertive learner 2
Being an independent & assertive learner 2Being an independent & assertive learner 2
Being an independent & assertive learner 2
SaKuchi Saku
 
10242021 Printhttpscontent.uagc.eduprintWinckelman.
10242021 Printhttpscontent.uagc.eduprintWinckelman.10242021 Printhttpscontent.uagc.eduprintWinckelman.
10242021 Printhttpscontent.uagc.eduprintWinckelman.
BenitoSumpter862
 

Similaire à Meher ppt (1) (20)

Informatics UG4 2006-7
Informatics UG4 2006-7Informatics UG4 2006-7
Informatics UG4 2006-7
 
Medical informatics
Medical informaticsMedical informatics
Medical informatics
 
How to become an effective web searcher
How to become an effective web searcherHow to become an effective web searcher
How to become an effective web searcher
 
Information literacy
Information literacyInformation literacy
Information literacy
 
Honors English - Surface
Honors English - SurfaceHonors English - Surface
Honors English - Surface
 
Electronic Databases
Electronic DatabasesElectronic Databases
Electronic Databases
 
Computer Science Library Training
Computer Science Library TrainingComputer Science Library Training
Computer Science Library Training
 
Database Terms Concepts2
Database Terms  Concepts2Database Terms  Concepts2
Database Terms Concepts2
 
Finding Articles @APL
Finding Articles @APLFinding Articles @APL
Finding Articles @APL
 
Informatics Transkills 2006-7
Informatics Transkills 2006-7Informatics Transkills 2006-7
Informatics Transkills 2006-7
 
Using eSearch and key databases
Using eSearch and key databasesUsing eSearch and key databases
Using eSearch and key databases
 
Computer Science Masters Library Training - June 2017
Computer Science Masters Library Training - June 2017Computer Science Masters Library Training - June 2017
Computer Science Masters Library Training - June 2017
 
Web of Science
Web of ScienceWeb of Science
Web of Science
 
TexShare Databases Basic Reference Lesson 1
TexShare Databases Basic Reference Lesson 1TexShare Databases Basic Reference Lesson 1
TexShare Databases Basic Reference Lesson 1
 
Database Basics2
Database Basics2Database Basics2
Database Basics2
 
Classics Information research skills for projects and dissertations
Classics Information research skills for projects and dissertationsClassics Information research skills for projects and dissertations
Classics Information research skills for projects and dissertations
 
Retrieval approches
Retrieval approchesRetrieval approches
Retrieval approches
 
Chapter 1 Introduction to ISR (1).pdf
Chapter 1 Introduction to ISR (1).pdfChapter 1 Introduction to ISR (1).pdf
Chapter 1 Introduction to ISR (1).pdf
 
Being an independent & assertive learner 2
Being an independent & assertive learner 2Being an independent & assertive learner 2
Being an independent & assertive learner 2
 
10242021 Printhttpscontent.uagc.eduprintWinckelman.
10242021 Printhttpscontent.uagc.eduprintWinckelman.10242021 Printhttpscontent.uagc.eduprintWinckelman.
10242021 Printhttpscontent.uagc.eduprintWinckelman.
 

Dernier

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Victor Rentea
 

Dernier (20)

FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
 
Understanding the FAA Part 107 License ..
Understanding the FAA Part 107 License ..Understanding the FAA Part 107 License ..
Understanding the FAA Part 107 License ..
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
AI+A11Y 11MAY2024 HYDERBAD GAAD 2024 - HelloA11Y (11 May 2024)
AI+A11Y 11MAY2024 HYDERBAD GAAD 2024 - HelloA11Y (11 May 2024)AI+A11Y 11MAY2024 HYDERBAD GAAD 2024 - HelloA11Y (11 May 2024)
AI+A11Y 11MAY2024 HYDERBAD GAAD 2024 - HelloA11Y (11 May 2024)
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
JohnPollard-hybrid-app-RailsConf2024.pptx
JohnPollard-hybrid-app-RailsConf2024.pptxJohnPollard-hybrid-app-RailsConf2024.pptx
JohnPollard-hybrid-app-RailsConf2024.pptx
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
 
WSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering DevelopersWSO2's API Vision: Unifying Control, Empowering Developers
WSO2's API Vision: Unifying Control, Empowering Developers
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptx
 

Meher ppt (1)

  • 2. INTRODUCTION • The incredible growth in the amount of electronic information that has become available in the last few years has made the ability to search & navigate these e-sources increasingly important. More often than not researching topic now includes using not only print sources, it also requires accessing information via the internet OPACS, CD-ROMS, & commercial databases such as westlaw, Firstserach, & Lexis.
  • 3. BASIC SEARCH TECHNIQUES 1. Keyword & Phrase search: A search can be conducted by using a single search term or a phrase comprising more than one term. Keyword search: e.g., “Library” Phrase Search: e.g., “library management”
  • 4. 2. Truncation Search: Truncation allows a search to be conducted for all the different forms of words having the same common roots. A number of different options are available for truncation: • Right truncation: E.g. compute* • Left truncation: E.g. *hyl will retrieve words like methyl, ethyl etc. • Internal truncation: E.g. col*r will retrieve both the terms colour & color.
  • 5. 3. PROXIMITY SEARCH Here it allows us to specify how close two or more words must appear in order to register a match. It is of 3 types: (a) Word proximity (b) Sentence proximity (c)Paragraph proximity (a) WORD PROXIMITY: E.g. “content collection”/4 It retrieve content & collection in 4 word difference. Ordered proximity: E.g. “content collection”/4 Unordered proximity: E.g. “content collection”@4
  • 6. (b)Sentence Proximity: A sentence proximity allow to search for term which must be in the same sentence. E.g. “Library management”/S (ORDERED) “Library management”@S (UNORDERED) These two word must be appear in the same sentence. (c)PARAGRAPH PROXIMITY: It allows to search which must be occurring in same paragraph. E.g. “Library automation”/P (ORDERED) “Library automation”@P (UNORDERED) These are two words must appear in same paragraph in it’s retrieval.
  • 7. 4. BOOLEAN SEARCH: Many search engine allow use of ‘AND’, ‘OR’ & ‘NOT’ to narrow or broaden a request. OPERATOR AND E.g. Library AND Automation The result will consist of documents that contain both words i.e. library & automation. OPERATOR OR E.g. Library OR Automation It retrieves maximum number of document because it retrieves document having library, having automation or both library and automation. OPERATOR NOT E.g. Library AND Automation NOT India It retrieves documents having the word “Library and Automation” but not having the word “India”.
  • 8. 5. LIMITING SEARCH: E.g. Document, published after 2000 E.g. Library Automation, pdf E.g. Birds nest, Hindi language. 6. FIELD SEARCH:  Title Search  URL Search  Link Search  File type Search