Best Paper Awards

The Best Paper Award is presented to the individual(s) judged by an awards committee to have written the best paper appearing in the annual conference proceedings.

Year Authors Citation
2022 Valeriia Bolotova
Vladislav Blinov
Falk Scholer
Bruce Croft
Mark Sanderson
A Non-Factoid Question-Answering Taxonomy
2021 Harrie Oosterhuis Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness
2020 Marco Morik
Ashudeep Singh
Jessica Hong
Thorsten Joachims
Controlling Fairness and Bias in Dynamic Learning-to-Rank
2019 Huazheng Wang
Sonwoo Kim
Eric McCord-Snook
Qingyun Wu
Hongning Wang
Variance Reduction in Gradient Exploration for Online Learning to Rank
2018 Rocío Cañamares
Pablo Castells
Should I Follow the Crowd? A Probabilistic Analysis of the Effectiveness of Popularity in Recommender Systems
2017 Bob Goodwin
Michael Hopcroft
Dan Luu
Alex Clemmer
Mihaela Curmei
Sameh Elnikety
Yuxiong He
BitFunnel: Revisiting Signatures for Search
2016 Yashar Moshfeghi
Peter Triantafillou
Frank E. Pollick
Understanding Information Need: an fMRI Study
2015 Claudio Lucchese
Franco Maria Nardini
Salvatore Orlando
Raffaele Perego
Nicola Tonellotto
Rossano Venturini
QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees
For a paper that develops a novel representation of binary regression trees based on bitvectors and an algorithm to perform a fast interleaved traversal of the trees in a cache-aware fashion, and demonstrates significant efficiency gains on publically available learning-to-rank data sets with various models that use ensembles of regression trees.
2014 Giuseppe Ottaviano
Rossano Venturini
Partitioned Elias-Fano indexes
For a paper that significantly improves on an already excellent compression technique, while preserving query time efficiency, as well as exhibiting the best compression ratio/processing speed trade-off.
2013 Ryen W. White Beliefs and Biases in Web Search
For a paper which explores the impact of pre-conceived biases when searching in the health domain using a combination of surveys, human labeling of search results, and large scale search log analysis.
2012 Mark Smucker
Charles Clarke
Time-based calibration of effectiveness measures
Selected for proposing a novel evaluation framework for IR where cumulative gain is computed with consideration of the time spent by users on examining search results, which enables better modeling of user effort in quantitative IR evaluation.
2011 Mikhail Ageev
Qi Guo
Dmitry Lagun
Eugene Agichtein
Find It If You Can: A Game for Modeling Different Types of Web Search Success Using Interaction Data
2010 Ryen W. White
Jeff Huang
Assessing the Scenic Route: Measuring the Value of Search Trails in Web Logs
2009 Jaime Arguello
Fernando Diaz
Jamie Callan
Jean-Francois Crespo
Sources of evidence for vertical selection
2008 Jeremy Pickens
Gene Golovchinsky
Chirag Shah
Pernilla Qvarfordt
Maribeth Back
Algorithmic Mediation for Collaborative Exploratory Search
2007 Ryen White
Mikhail Bilenko
Silviu Cucerzan
Studying the Use of Popular Destinations to Enhance Web Search Interaction
2006 Ben Carterette
James Allan
Ramesh Sitaraman
Minimal Test Collections for Retrieval Evaluation
2005 Elad Yom-Tov
Shai Fine
David Carmel
Adam Darlow
Learning to Estimate Query Difficulty (Including Applications to Missing Content Detection and Distributed Information Retrieval)
2004 Hui Fang
Tao Tao
ChengXiang Zhai
A Formal Study of Information Retrieval Heuristics
2003 Ian Ruthven Re-examining the potential effectiveness of interactive query expansion
2002 Yi Zhang
Jamie Callan
Thomas Minka
Novelty and redundancy detection in adaptive filtering
2001 James Allan
Rahul Gupta
Vikas Khandelwal
Temporal Summaries of News Topics
2000 Kalervo Järvelin
Jaana Kekäläinen
IR evaluation methods for retrieving highly relevant documents.
1999 Jian-Yun Nie
Michel Simard
Pierre Isabelle
Richard Durand
Cross-language information retrieval based on automatic mining of parallel texts from the web
1998 Warren Greiff A theory of term weighting based on exploratory data analysis
1997 H.T. Ng
W.B. Goh
K.L. Low
Feature selection, perceptron learning, and a usability case study for text categorization
1996 G.J.F. Jones
J.T. Foote
Karen Spärck Jones
S.J. Young
Retrieving spoken documents by combining multiple index sources

Honorable Mentions

Year Authors Citation
2022 Harrisen Scells
Shengyao Zhuang
Guido Zuccon
Reduce, Reuse, Recycle: Green Information Retrieval Research
2021 Yang Zhang
Fuli Feng
Xiangnan He
Tianxin Wei
Chonggang Song
Guohui Ling
Yongdong Zhang
Causal Intervention for Leveraging Popularity Bias in Recommendation
2020 Fan Zhang
Jiaxin Mao
Yiqun Liu
Xiaohui Xie
Weizhi Ma
Min Zhang
Shaoping Ma
Models Versus Satisfaction: Towards a Better Understanding of Evaluation Metrics
2019 Xu Lu
Lei Zhu
Zhiyong Cheng
Liqiang Nie
Huaxiang Zhang
Online Multi-modal Hashing with Dynamic Query-adaption
2017 Jun Wang
Lantao Yu
Weinan Zhang
Yu Gong
Yinghui Xu
Benyou Wang
Peng Zhang
Dell Zhang
IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models
2017 Fumin Shen
Yadong Mu
Yang Yang
Wei Liu
Li Liu
Jingkuan Song
Heng Tao Shen
Classification by Retrieval: Binarizing Data and Classifiers
2016 Ido Guy Searching by Talking: Analysis of Voice Queries on Mobile Web Search
2016 Hanwang Zhang
Fumin Shen
Wei Liu
Xiangnan He
Huanbo Luan
Chua Tat-Seng
Discrete Collaborative Filtering
2015 Eddy Maddalena
Stefano Mizzaro
Falk Scholer
Andrew Turpin
The Benefits of Magnitude Estimation for Relevance Assessment
2015 Carsten Eickhoff
Sebastian Dungs
Vu Tran
An Eye-Tracking Study of Query Reformulation
2015 Chao Wang
Yiqun Liu
Meng Wang
Ke Zhou
Jian-Yun Nie
Shaoping Ma
Incorporating Non-sequential Behavior into Click Models
2014 Leif Azzopardi Modelling interaction with economic models of search