Agglomerative clustering of a search engine query log
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Clustering user queries of a search engine
Proceedings of the 10th international conference on World Wide Web
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
ACM SIGIR Forum
Optimizing web search using web click-through data
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Evaluating implicit measures to improve web search
ACM Transactions on Information Systems (TOIS)
Accurately interpreting clickthrough data as implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Co-active intelligence for image retrieval
Proceedings of the 13th annual ACM international conference on Multimedia
LA-WEB '05 Proceedings of the Third Latin American Web Congress
Learning user interaction models for predicting web search result preferences
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Scalable relevance feedback using click-through data for web image retrieval
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Evaluating the accuracy of implicit feedback from clicks and query reformulations in Web search
ACM Transactions on Information Systems (TOIS)
The influence of caption features on clickthrough patterns in web search
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Random walks on the click graph
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
An experimental comparison of click position-bias models
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
A user browsing model to predict search engine click data from past observations.
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
A dynamic bayesian network click model for web search ranking
Proceedings of the 18th international conference on World wide web
Click chain model in web search
Proceedings of the 18th international conference on World wide web
Mining web query hierarchies from clickthrough data
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Are Clickthroughs Useful for Image Labelling?
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Image annotation using clickthrough data
Proceedings of the ACM International Conference on Image and Video Retrieval
Classifying Images with Image and Text Search Clickthrough Data
AMT '09 Proceedings of the 5th International Conference on Active Media Technology
Using clicks as implicit judgments: expectations versus observations
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Investigating the effectiveness of clickthrough data for document reordering
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Incorporating post-click behaviors into a click model
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Implicit association via crowd-sourced coselection
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
Overview of the ImageCLEF 2006 photographic retrieval and object annotation tasks
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
Why not, WINE?: towards answering why-not questions in social image search
Proceedings of the 21st ACM international conference on Multimedia
Finding synonyms and other semantically-similar terms from coselection data
AWC '13 Proceedings of the First Australasian Web Conference - Volume 144
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The interactions of users with search engines can be seen as implicit relevance feedback by the user on the results offered to them. In particular, the selection of results by users can be interpreted as a confirmation of the relevance of those results, and used to reorder or prioritize subsequent search results. This collection of search/result pairings is called clickthrough data, and many uses for it have been proposed. However, the reliability of clickthrough data has been challenged and it has been suggested that clickthrough data are not a completely accurate measure of relevance between search term and results. This paper reports on an experiment evaluating the reliability of clickthrough data as a measure of the mutual relevance of search term and result. The experiment comprised a user study involving over 67 participants and determines the reliability of image search clickthrough data, using factors identified in previous similar studies. A major difference in this work to previous work is that the source of clickthrough data comes from image searches, rather than the traditional text page searches. Image search clickthrough data were rarely examined in prior works but has differences that impact the accuracy of clickthrough data. These differences include a more complete representation of the results in image search, allowing users to scrutinize the results more closely before selecting them, as well as presenting the results in a less obviously ordered way. The experiment reported here demonstrates that image clickthrough data can be more reliable as a relevance feedback measure than has been the case with traditional text-based search. There is also evidence that the precision of the search system influences the accuracy of click data when users make searches in an information-seeking capacity. © 2012 Wiley Periodicals, Inc.