An evaluation of retrieval effectiveness for a full-text document-retrieval system
Communications of the ACM
Web search behavior of Internet experts and newbies
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Differences between novice and experienced users in searching information on the World Wide Web
Journal of the American Society for Information Science - Special topic issue: individual differences in virtual environments
Domain-specific search strategies for the effective retrieval of healthcare and shopping information
CHI '02 Extended Abstracts on Human Factors in Computing Systems
Eye-tracking analysis of user behavior in WWW search
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
LA-WEB '05 Proceedings of the Third Latin American Web Congress
Enriching the knowledge sources used in a maximum entropy part-of-speech tagger
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
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
Investigating behavioral variability in web search
Proceedings of the 16th international conference on World Wide Web
Robust classification of rare queries using web knowledge
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Inferring semantic query relations from collective user behavior
Proceedings of the 17th ACM conference on Information and knowledge management
Characterizing the influence of domain expertise on web search behavior
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Proceedings of the 18th international conference on World wide web
Exploratory information search by domain experts and novices
Proceedings of the 15th international conference on Intelligent user interfaces
Studying trailfinding algorithms for enhanced web search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Assessing the scenic route: measuring the value of search trails in web logs
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Query suggestion for E-commerce sites
Proceedings of the fourth ACM international conference on Web search and data mining
Recommender systems at the long tail
Proceedings of the fifth ACM conference on Recommender systems
Rewriting null e-commerce queries to recommend products
Proceedings of the 21st international conference companion on World Wide Web
Chelsea won, and you bought a t-shirt: characterizing the interplay between Twitter and e-commerce
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
On segmentation of eCommerce queries
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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User expectation and experience for web search and eCommerce (product) search are quite different. Product descriptions are concise as compared to typical web documents. User expectation is more specific to find the right product. The difference in the publisher and searcher vocabulary (in case of product search the seller and the buyer vocabulary) combined with the fact that there are fewer products to search over than web documents result in observable numbers of searches that return no results (zero recall searches). In this paper we describe a study of zero recall searches. Our study is focused on eCommerce search and uses data from a leading eCommerce site's user click stream logs. There are 3 main contributions of our study: 1) The cause of zero recall searches; 2) A study of user's reaction and recovery from zero recall; 3) A study of differences in behavior of power users versus novice users to zero recall searches.