search and rescue repair strategies of remote users searching the online catalog nancy b. turner,...
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![Page 1: Search and Rescue Repair Strategies of Remote Users Searching the Online Catalog Nancy B. Turner, Electronic Resources Librarian, Syracuse University Susan](https://reader036.vdocument.in/reader036/viewer/2022062717/56649e375503460f94b27d07/html5/thumbnails/1.jpg)
Search and Rescue
Repair Strategies of Remote Users Searching the Online Catalog
Nancy B. Turner, Electronic Resources Librarian, Syracuse University Susan E. Beck, Head of Reference & Research Services, New Mexico State University
Eighth Annual Reference Research Forum, American Library Association Annual Conference,
Atlanta, June 16, 2002
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Research Questions
Do users in remote locations repair searches?
What types of repair strategies do they employ?
How can this information inform our work as reference librarians?
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Transaction Logs
Traditional OPAC LogsWeb Server LogsAppropriate UsesDrawbacks
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User Population
Carnegie I—Research Extensive/ Hispanic Serving
15,000 enrollmentDoctoral degrees in
5 colleges: Agriculture, Arts & Sciences, Business, Education, Engineering
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Physical Environment
Two library buildings: Branson & Zuhl
Two periodicals areasTwo reference desk areasTwo stack areas
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Endeavor catalog
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Search Screen
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Methodology: Data collection
Apache server log extraction 7 two hour intervals over 3 month period Various times: am, pm, weekends
Created Library IP address map Charted search locations by IP address:
Campus (NMSU domain) Off campus (non-NMSU domain) Staff Zuhl & Branson public service areas
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Methodology: Data treatment I
Text files imported to spreadsheetImported three columns only
IP address, Date/Time, Search QueryMapped IP’s to library locationsSelected only unmediated, remote
locations to reviewDivided spreadsheet into 3
worksheets All, Unmediated, Staff
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Methodology: Data Treatment II
Search_Code = TALL replaced with Search=TitleSearch_Code = JALL replaced with Search=Journal TitleSearch_Code = FT*& replaced with Search=Keyword Search_Code=NAME replaced with Search=AuthorSearch_Code=SUBJECT replaced with Search=SubjectSearch_Code=CALL replaced with Search=Call Number
%2B = replaced with + %3F = replaced with ?%3A = replaced with : %2C= replaced with , %27 = replaced with ‘ %22 = replaced with “
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Cgi search syntax translation
1. GETSearch_Arg=tankers+full+of+trouble&Search_ Code=TALL&PID=19913&SEQ=20020314130448&CNT=25&HIST=1&SEARCH_FROM_TITLES_PAGE
2. GETSearch_Arg=tankers full of trouble &Search=TITLE &PID=19913&SEQ= 20020314130448&CNT=25&HIST=1&SEARCH_FROM_ TITLES_PAGE
User searching for the title, “Tankers full of trouble” from the Titles display listing page
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Search query translation
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Methodololgy: Data Treatment III
Selected “searches” based on
syntax GETSearch_Arg=
Coded searches by search type JT, T, S, A, CN, B, K, C
Tallied searches by type & area
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March 14 Tallies
Bran Per 0 0 0 0 0 0 0 0 0 0Bran Ref 269 88 10 21 3 21 6 27 0 0Bran Stacks 53 28 0 4 6 4 13 0 1 0Campus 421 177 28 31 37 42 25 14 0 0Off Campus 111 30 5 7 2 7 9 0 0 0Zuhl Per 19 9 0 2 1 5 1 0 0 0Zuhl Ref 259 93 6 14 4 25 38 6 0 0Zuhl Stacks 122 41 1 0 0 26 11 3 0 0Total: 1254 466 50 79 53 130 103 50 1 0All Users: 2353Unmediated Inputs % 53
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GETSearch_Arg=new mexico litter controll&Search=Keyword
GETv1=1&ti=1,1&Search_Arg=new mexico litter controll&Search=Keyword
GETti=21,0&Search_Arg=new mexico litter controll&Search=Keyword
GETPAGE=sbSearch
GETSearch_Arg=new mexico litter&Search=Keyword
GETti=11,0&Search_Arg=new mexico litter&Search=Keyword
GETti=21,0&Search_Arg=new mexico litter&Search=Keyword
GETti=31,0&Search_Arg=new mexico litter&Search=Keyword
GETSearch_Arg=texas litter&Search=Keyword
GETSearch_Arg=texas litter laws&Search=Keyword
GETSearch_Arg= litter laws&Search=Keyword
Excerpt from search log
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Data Analysis
After coding all discrete searches, we then re-coded those searches based on repair types.
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Search Repair Levels
WordRepairs occur at word level
ConceptRepairs involve the concept(s)
searched. A concept is typically multi-word or a phrase. It can be multi-concept
SearchRepairs show knowledge of search types
or knowledge of formatting within search types
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Word Level Repairs
Spelling (WS) multi-meter multimeter
18th eighteenth
Plural/Singular (WP) duns dun groups group
Capitalization (WC) Doll doll
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Word Level Example
GETSearch_Arg=bertrand russel& Search=Keyword
GETSearch_Arg=bertrand russell& Search=Keyword
GET Search_Arg=raceism in unimployment &Search=Keyword &
GET Search_Arg=racism in imployment &Search=Keyword
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Concept Level RepairsPunctuation: Add/drop punctuation (CP)
city of ladies “city of ladies”
christine pisan pisan, christine
Broaden: Drop concept/word (CB)
How to use a digital multimeters digital multimeters
Pregnancy—week by week Pregnancy
Change to another concept (CC)
English Men & Manners in the Eighteenth Century 18th Century British Women
Decline and Fall of Rome Edward Gibbon
Narrow: Add concept/word (CN)
“puerto rico” “puerto rico” “English”
pizan pizan city of ladies
Rephrase (CR) English Society in the 18th Century Daily Life in Eighteenth Century England
Ireland travel Ireland guidebook
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Concept Level Example
GETSearch_Arg=Patton&Search=Keyword GETSearch_Arg=General Georgo Patton &Search
=Keyword (CN)GETSearch_Arg=Leadership&Search=Subject (CC)GETSearch_Arg=Military Leadership& Search =Subject
(CN, STGETSearch_Arg=General Patton leadership&
Search=Subject (CN)GETSearch_Arg=George Patton leadership&
Search=Subject (CR)GETSearch_Arg=Leadership style of George Patton&
Search=Subject (CR, CN)
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Search Level Repairs
Invert words/names (SI)
Edward Gibbon Gibbon, Edward
Add/drop article (SA) A Doll House Doll House
Switch search type (ST)
A Doll House (Subject) A Doll House (Title)
tf 140 s73 (Keyword) tf 140 s73 (Call Number)
Limit search (SL) Home care home care (limited to specific library location or format or language, etc.)
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Search Level Example I
GET Search_Arg=child abuse laws&Search=Keyword GET Search_Arg=child abuse laws& Search=Subject
GET Search_Arg=Troy Boone&Search=AuthorGET Search_Arg=Boone, Troy&Search=Author
GET Search_Arg=A Doll House&Search=TitleGET Search_Arg=Doll House&Search=Title
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Search Level Example II
GET Search_Arg=Babylonian Mathematics and the Plimpton 322&Search= Keyword
GET Search_Arg=Babylonian Mathematics and the Plimpton 322&Search= Subject
GET Search_Arg=Babylonian Mathematics and the Plimpton 322&Search= Title
…2 minutes pass…
GET Search_Arg=History of Babylonian Mathematics&Search=Title GET Search_Arg=History of Babylonian Mathematics&Search=Journal Title GET Search_Arg=History of Babylonian Mathematics&Search=Subject GET Search_Arg=History of Babylonian Mathematics& Search= Keyword
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Preliminary findings: Search types
Although no specific search type emerges as an obvious favorite
Keyword 28% Jrnl Title 15%Subject 19% Author 10%Title 16% Boolean 9%
Call # 3%
44% of all searches are for known items (title, journal title, author & call number)
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Preliminary findings: Word level repairs
Repair Code Repair Type TOTAL %
WS Spelling 81 8%WP Plural/Singular 13 1%WC Capitalization 21 2%Total Word Level Repairs 115 12%
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Preliminary findings: Concept level repairs
Repair Code Repair Type TOTAL %
CPPunctuation: Add/drop punctuation 30 3%
CB Change to broader concept 116 12%CC Change to another concept 89 9%CN Narrow: Add concept/word 132 14%CR Rephrase 136 14%Total Concept Level Repairs 503 52%
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Preliminary findings: Search level repairs
Repair Code Repair Type TOTAL %
SI Invert words/names 22 2%SA Add/drop article 7 1%ST Switch search type 270 28%SL Limit search 17 2%SB Boolean Syntax Change 26 3%Total Search Level Repairs 342 36%
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Preliminary findings: Overall repairs
Repair Code Repair Type TOTAL
Total Repairs 960 87%R Repeat Searches 145 13%
Total Redone/Repaired 1105
Total Searches 2132
% Searches Repaired 45%% Searches Redone 52%
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Preliminary findings
Over 50% catalog uses are non-staff Unassisted user searches.…………….56% Staff/Mediated user searches………..44%
Higher incidence of concept level repairs than word and search level
Preferred repair strategy is to switch search types
High incidence of retyping exact search
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Further study
Extend data collection time periods Increase # of data collection
sessionsInclude different user population Extend analysis to include
Length of time spent repairing search Search types leading to more repairs Number of repairs made per search
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Questions?
For more information, contact:
Nancy B. Turner at [email protected] E. Beck at [email protected]