activity
20162026
most citedEvaluating Stochastic Rankings with Expected Exposure

176 citations · 914 across the 61 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.IR2022★ 22 cited

Result Diversification in Search and Recommendation: A Survey

Haolun Wu, Yansen Zhang, Chen Ma +4

Diversifying return results is an important research topic in retrieval systems in order to satisfy both the various interests of customers and the equal market exposure of provide…

cs.HC2022★ 1 cited

Ethical and Social Considerations in Automatic Expert Identification and People Recommendation in Organizational Knowledge Management Systems

Ida Larsen-Ledet, Bhaskar Mitra, Siân Lindley

Organizational knowledge bases are moving from passive archives to active entities in the flow of people's work. We are seeing machine learning used to enable systems that both col…

cs.IR2022★ 2 cited

Are We There Yet? A Decision Framework for Replacing Term Based Retrieval with Dense Retrieval Systems

Sebastian Hofstätter, Nick Craswell, Bhaskar Mitra +2

Recently, several dense retrieval (DR) models have demonstrated competitive performance to term-based retrieval that are ubiquitous in search systems. In contrast to term-based mat…

cs.IR2022★ 1 cited

Joint Multisided Exposure Fairness for Recommendation

Haolun Wu, Bhaskar Mitra, Chen Ma +2

Prior research on exposure fairness in the context of recommender systems has focused mostly on disparities in the exposure of individual or groups of items to individual users of…

cs.IR2022

Less is Less: When Are Snippets Insufficient for Human vs Machine Relevance Estimation?

Gabriella Kazai, Bhaskar Mitra, Anlei Dong +2

Traditional information retrieval (IR) ranking models process the full text of documents. Newer models based on Transformers, however, would incur a high computational cost when pr…