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presentation
A"Survey"on"Temporal"Web"
Search"Experience
Hideo"Joho1,"Adam"Jatowt2,"and"Roi"Blanco3"
1University"of"Tsukuba,"Japan"
2Kyoto"University,"Japan"
3Yahoo!"Research,"Barcelona,"Spain
2013/05/13
TempWeb"2013
Outline
• 
• 
• 
• 
• 
• 
• 
MoNvaNon"
Data"CollecNon"Method"
Gross"StaNsNcs"
CorrelaNon"→"Breakdown"
"(Some)"QualitaNve"Results"
Discussion"
Summary
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TempWeb"2013
MoNvaNon
•  Much"of"research"on"temporal"search"focuses"
on"log"analyses"or"system"development"
•  A"broader"and"deeper"understanding"of"
people’s"temporal"informaNon"seeking"
behaviour"can"facilitate"the"community"
–  Morris"[11]"for"collaboraNve"search"
–  Ed"and"Chi"[5]"for"social"search"
•  Let’s"ask"people!"
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Data"CollecNon"Method"1
•  CriNcal"Incident"Analysis"
–  Asking"people"to"describe"a"prominent"experience"
–  Usually"carried"out"via"interviews"
–  Evans"&"Chi"[5]"applied"to"quesNonnaires"
•  18"QuesNons"
–  Most"recent"web"search"experience"
–  15"closed"and"3"open"quesNons"(Broad"scope)"
–  Contexts,"InformaNon"Needs,"Process,"Outcomes
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Data"CollecNon"Method"2
•  110"ParNcipants"in"Japan"
–  11"Females"+"11"Males"/"20s"–"60s"Blocks"
–  Filtered"by"a"search"experience"within"3"days"
–  48%"single,"52%"married"
–  Selfgreported"occupaNons"
•  Office"Workers"(36),"Homemakers"(21)"PartgNme"
workers"(15),"University"Students"(8),"Others"(16),"
Managers"(2)"
•  Mostly"quanNtaNve"analyses"so"far"
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Context:"When
3%"
1%"
15%"
43%"
38%"
Mostly"fresh"memories
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<"1"hour"
<"1"day"
Yesterday"
<"2"days"
>"2"days"
Context:"Where
2%"
2%"
17%"
79%"
Very"indoor
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Home"
Office"
Transport"
Outdoor"
Context:"How
15%"
35%"
50%"
Mixed"devices
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Desktop"PC"
Laptop"/"Tablet"
Mobile"
Info"Needs:"Target"Time
60"
53"
50"
40"
30"
20"
10"
9"
0"
5"
0"
9"
2"
12"
9"
2"
1"
Recency"is"important
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5"
0"
1"
1"
0"
1"
Info"Needs:"Seasonal"Interests
14%"
41%"
24%"
21%"
76%"is"some"kind"of"temporal"needs
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Long"Term"
Seasonal"
Recent"
Other"
Info"Needs:"Fresh,"Regfind,"Tech
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Process:"Search"Time
3%" 3%"
14%"
4%"
45%"
31%"
Nothing"unusual?
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<"5"min"
5"g"10"min"
10"g"30"min"
30"min"g"1h"
>"1h"
N/A"
Process:"Difficulty
9%"
32%"
24%"
Website"
Query"
Search"Results"
None"
35%"
2/3"sNll"have"a"difficulty"(in"general)
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Outcome:"Found?
2%"
23%"
75%"
Yes"
ParNally"
No"
Yet"managed"to"find"relevant"informaNon
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Outcome:"SaNsfacNon
2%"
15%"
13%"
70%"
SNll"17%"are"not"happy
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Very"SaNsfied"
SaNsfied"
Either"
Not"SaNsfied"
Outcome:"InformaNon"Use
30"
35%"was"not"used"within"a"day
28"
26"
25"
21"
20"
18"
15"
9"
10"
5"
2"
2"
2"
<"1M"
<"nM"
1"
1"
<"1Y"
<"nY"
0"
0"(Now)" <"1D"
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<"nD"
<"1W"
<"nW"
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No"Plan"
CorrelaNon
Focusing"on"some"of"significant"pairs
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LocaNon"vs."Target"Time
Recent"informaNon"when"outside"or"stops
No"future"informaNon"sought"from"offices
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Technicality"vs."Seasonal
Technical"informaNon"tends"to"be"longgterm"or"
recent"interests
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Freshness"vs."Technicality
Freshness"is"important"for"general"not"technical
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Regfinding"vs."Freshness
Regfinding"is"likely"to"prefer"fresh"informaNon
Cannot"tell"for"firstgNme"search
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Regfinding"vs."Seasonal
First"Nme"search"is"likely"to"prefer"recent"info
Cannot"tell"for"regfinding"search
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Technicality"vs."Target"Time
No"future"informaNon"sought"by"technical"needs
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QualitaNve"analyses
• 
• 
• 
• 
A"lot"of"TV"is"going"on"
A"lot"of"Internet"browsing"is"going"on"
Weak"informaNon"needs"
Future"temporal"expression"can"be"difficult"
–  Project"X"is"supposed"to"complete"by"the"end"of"
January"2015."
–  Temporal"incidents"in"ficNons
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Summary
•  QuesNonnairegbased"CIA"was"carried"out"to"gain"
broader"&"deeper"understanding"of"temporal"
informaNon"seeking"behaviour"
•  Results"reinforcing"the"importance"of"recency"needs"
•  "Seasonal"interests,"technicality,"target"Nme,"regfinding,"
and"freshness"can"all"interplay"to"affect"people’s"
temporal"search"behaviour."
•  How"can"we"deal"with"the"gap"between"search"and"
use?"
•  Smaller"proporNon"of"future"informaNon"search"is"
natural"cause"or"lack"of"advancement?"
2013/05/13
TempWeb"2013
References
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Workshop,$2011.""
K."Berberich,"S."Bedathur,"O."Alonso,"and"G."
Weikum."A"Language"Modeling"Approach"for"
Temporal"InformaNon"Needs."In"ECIR$2010,$
pages"13–25,"2012.""
K."Berberich,"S."Bedathur,"T."Neumann,"and"G."
Weikum."A"Time"Machine"for"Text"Search."In"
SIGIR$2007,$pages"519–526,"2007.""
R."Campos,"G."Dias,"and"A.M."Jorge."An"
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B."M."Evans"and"E."H."Chi."An"elaborated"model"
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R."Jones"and"F."Diaz."Temporal"profiles"of"
queries."ACM$Transac?ons$on$Informa?on$
Systems,$25(3):656–678,"2007.""
N."Kanhabua,"and"K."Nørvåg."Determining"Time"
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A."Khodaei,"and"O."Alonso."Temporallyg
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A."Kulkarni,"J."Teevan,"K.M."Svore"and"S.T."
Dumais."Understanding"temporal"query"
dynamics."In"WSDM$2011,$pages"167–176."
D."Metzler,"R."Jones,"F."Peng,"and"R."Zhang."
Improving"search"relevance"for"implicitly"
temporal"queries."In"SIGIR$2009,$2009."
Morris,"M.R."A"survey"of"collaboraNve"web"
search"pracNces."In"SIGCHI$2008,$pages"
1657–1660,"2008."
S."Nunes,"C."Ribeiro"and"G."David."Use"of"
temporal"expressions"in"web"search."In"
ECIR$2008,$pages"580–584,"2008."
M."Shokouhi."DetecNng"seasonal"queries"
by"Nmegseries"analysis."In"SIGIR$2011,$
pages"1171–1172,"2011."
J."Teevan"and"E."Adar."InformaNon"reg
retrieval:"repeat"queries"in"yahoo’s"logs."In"
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