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A Study of Awareness in Multimedia Search. Robert Villa, Nick Gildea, Joemon Jose Information Retrieval Group April 2008. Overview. Introduction Collaboration and awareness in search Research questions Experimental study Inducing awareness: a game scenario Video retrieval
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A Study of Awareness in Multimedia Search Robert Villa, Nick Gildea, Joemon Jose Information Retrieval Group April 2008
Overview • Introduction • Collaboration and awareness in search • Research questions • Experimental study • Inducing awareness: a game scenario • Video retrieval • Demo of multimedia retrieval system • Some results • Conclusions
Information Retrieval • Deals with practical and theoretical models of searching unstructured collections of documents • Idealised aim: supply the system with a natural language description of your need • The system returns a ranked list of the documents relevant to your need • Process is naturally probabilistic and uncertain
Video retrieval • Video retrieval systems index and search collections of videos • Like traditional IR, the indexing of the video data is assumed to be automatic • Extraction of visual or audio features • Use of automatic speech recognition • Queries are typically textual or by example
Video retrieval • Videos are automatically split into ‘shots’ (shot segmentation) • Shot boundaries are determined using the visual content of video frames • Each shot is a short element of a video • in TRECVID 2006, typically 2 to 3 seconds, although there are some much longer shots • Shots are the element of retrieval • Where a text system retrieves documents, video retrieval systems retrieve shots
Example of a shot • Every shot has an associated text transcript: • E.g. “A dramatic arrival” • Generated by Automatic Speech Recognition (ASR) • Transcript can often be very wrong
Collaborative Retrieval • Most current search systems assume searching is a solitary activity • Is this always the case, or can collaborative searching with one or more others be effective? • Rather than focus on collaboration in general, we decided to look at only one aspect of collaboration - awareness
Awareness • Awareness enables an “understanding of the activities of others”, an important aspect of collaboration • Paul Dourish and Victoria Bellotti. “Awareness and Coordination in Shared Workspaces”, CSCW'92 • Scenario: • Two users are searching on the same task at the same time in different places • Synchronous and remote
Previous work – collaborative search • Cerchiamo (FXPAL, Xerox) • Adcock et. al., in TRECVID 2007 • Two people collaborating, one a “gatherer” and the other a “reviewer” • SearchTogether (Microsoft) • Morris, M. R. (2007) • Provides a messaging system, recommending a web page to another, query awareness, etc. • Fischlar-DiamondTouch (DCU) • Smeaton et. al. (2007) • Table-top display which allows two people to work around it
Research question • Can awareness of another searcher aid a user when carrying out a multimedia search? • Will their performance increase? • Will less effort be needed to reach a given performance? • Shots played, browsing required • Will the user’s search behaviour change? • Number of queries executed, shots found independently
Competitive game scenario • We wanted to evaluate the effect of awareness in a “best case” scenario • i.e. a situation where there was some benefit to users in being aware of another’s actions • A competitive game scenario was used, where pairs of users competed to “win” the search tasks
Aim of the ‘game’ • The aim of the ‘game’ was to find as many relevant shots as possible for the task • Domain was video retrieval, where users had to search a video collection for ‘shots’ • Whoever finds the most shots ‘wins’ • A monetary award was given to the winner
System • Our existing video retrieval system was modified to allow collaboration • Each user could be given a view of the other user’s search screen • This was designed to work with two monitors: • The user’s own search interface on one screen • The other screen optionally showing the other user’s search screen • We supported 4 different situations
“Mutually Aware” User B User A A can see B’s screen and B can see A’s screen
“A aware of B” User B User A A can watch B’s screen while B cannot watch A
“B aware of A” User B User A B can watch A’s screen while A cannot watch B
“Independent” User B User A Both A and B cannot watch each other
Local search interface
Shots to use in relevance feedback
Result shots for the user
Remote search interface
User cannot see the other user’s final results – only a count of the number of shot currently marked by the user
This screen does not update automatically, theuser must pressthe “Refresh”button to update the screen
Video browser • Simple video browser pop’s up when the user clicks a keyframe • Allows the user to view the shot, and move backwards and forwards in the video
Conditions • From the point of view of an individual user: • Working independently • Cannot watch the other user, and knows that the other user can watch him/her • Can watch the other user, and knows that the other user cannot watch him/her • Can watch the other user, and knows that the other user can watch him/her
TRECVID 2006 Collection • Almost 260 hours of mostly news data from the end of 2005 • CNN, LBC, CCN, etc. • Multilingual (English, Chinese and Arabic) • Has a standard shot segmentation • ASR transcripts provided • For Chinese and Arabic video, also automatically translated into English
TRECVID 2006 Topics • 24 topics, of which we used the 4 worst performing overall from the interactive track • Hoped that these would be a similar challenge for the user • Adcock et al. (2007) found that users collaborated better on difficult tasks
Experimental design • Within user study was carried out • Latin square design • 4 tasks • 4 conditions • 24 users (12 pairs)
Procedure • Users took part in pairs • Users had 15 minutes to find as many shots as possible • At the end of the 4 tasks, the “winner” was announced • Each user was paid £10 • Winner got an extra £5, shared if there was a draw
Results • 12 competitive runs • 11 wins and 1 draw • And there was an immediate issue with one of the user’s ...
Search Performance • No significant difference found between the level of performance in the four different conditions • Overall performance was very low (typical in video IR, for these hard topics) • Performance does vary widely across the four tasks • Tasks 189 and 192 performed worst
Search behaviour: queries • Do users execute more queries searching alone? • Significant variation between watching and Independent was found
Number of shots found independently • Significant interaction was found between Independent and Watching
Changes in search behaviour • Users searched less when watching someone else • Also less searching executed in the watched condition (not significant) • Users found more shots themselves when watching someone else • Also found more shorts in the mutual and watched conditions, but not significant
Search terms used • One possible way awareness may help is by providing a user with new terms with which to use in queries • Did users copy search terms from the remote user? • We could not directly record this in the logs (terms are easily retyped)
Estimating copied search terms • Search terms which could have been copied were derived from the logs • Method: • Found the set of common terms • Found who used that term first • Checked for a click of the “refresh” button by the user who was second • Assumed that second user could have then copied that term
Copied terms • Suggests that a user is able to reuse search terms used by the other user
Searcher effort • Recorded three types of events to gauge searcher effort • Play events when a user clicks a shot • Move to next shot in video • Move to previous shot in video • Only significant relationship: • Watching and Watched and move to previous shot
Where did a user’s final results come from? • From the interface, we logged the user dragging and dropping shots between the different parts of the interface • We could record when someone copied a shot from the other user • Using this, we can estimate where user’s got their final results • (roughly!)
Conclusions • Despite the game scenario, users didn’t copy other people’s shots much • This came as something as a surprise • There’s no significant increase in a user’s performance • Only a trend ... • There is evidence that user’s do reuse search terms • 10 and 13% of terms are potentially copied
Conclusions • Results from user effort were unclear • Only significantly less interaction in one event