Journal of the American Society for Information Science - Special topic issue on the history of documentation and information science: part II
The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Online trust and reputation systems
Proceedings of the 8th ACM conference on Electronic commerce
An axiomatic approach for result diversification
Proceedings of the 18th international conference on World wide web
Efficient Computation of Diverse Query Results
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Relevance criteria for e-commerce: a crowdsourcing-based experimental analysis
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Beyond relevance in marketplace search
Proceedings of the 20th ACM international conference on Information and knowledge management
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The notion of relevance is key to the performance of search engines as they interpret the user queries and respond with matching results. Online search engines have used other features beyond pure IR features to return relevant matching documents. However, over-emphasis on relevance could lead to redundancy in search results. In document search, diversity is simply the variety of documents that span the result set. In an online marketplace the diversity in the result set is represented by items for sale by different sellers at different prices with different sales options. For such a marketplace, in order to minimize query abandonment and the risk of dissatisfaction to the average user, several factors like diversity, trust and value need to be taken into account. Previous work in this field [4] has shown an impossibility result that there exists no such function that can optimize for all these factors. Since these factors and the measures associated with the factors could be subjective we take an approach of giving the control back to the user. In this paper we describe an interface which enables users to have more control over the optimization function used to present the results. We demonstrate this for search on eBay - one of the largest online marketplaces with a vibrant user community and dynamic inventory. We use an algorithm based on bounded greedy selection [5] to construct the result set based on parameters specified by the user.