Filip Radlinski

发表

Active exploration for learning rankings from clickthrough data

Filip Radlinski, Thorsten Joachims, T. Joachims, 2007, KDD '07.

Fighting search engine amnesia: reranking repeated results

Milad Shokouhi, Filip Radlinski, Ryen W. White, 2013, SIGIR.

Inferring and using location metadata to personalize web search

Filip Radlinski, Ryen W. White, Paul N. Bennett, 2011, SIGIR.

Common Conversational Community Prototype: Scholarly Conversational Assistant pdf

Filip Radlinski, Matthias Hagen, Martin Potthast, 2020, ArXiv.

Online Evaluation for Information Retrieval

Filip Radlinski, Katja Hofmann, Lihong Li, 2016, Found. Trends Inf. Retr..

Simple Personalized Search Based on Long-Term Behavioral Signals

Filip Radlinski, M. de Rijke, Maarten de Rijke, 2017, ECIR.

Transparent, Scrutable and Explainable User Models for Personalized Recommendation

Filip Radlinski, Krisztian Balog, Shushan Arakelyan, 2019, SIGIR.

Online Search Evaluation with Interleaving

Filip Radlinski, 2015, WWW.

Query chains: learning to rank from implicit feedback pdf

Filip Radlinski, Thorsten Joachims, T. Joachims, 2005, KDD '05.

Optimizing relevance and revenue in ad search

Filip Radlinski, Andrei Z. Broder, Evgeniy Gabrilovich, 2008 .

First International Workshop on Conversational Approaches to Information Retrieval (CAIR'17)

Milad Shokouhi, Filip Radlinski, Hideo Joho, 2017, SIGIR.

Where Can I Buy a Boulder?: Searching for Offline Retail Locations

Filip Radlinski, Ryen W. White, Sandro Bauer, 2016, WWW.

Cost-Sensitive Machine Learning for Information Retrieval

Filip Radlinski, Martin Szummer, Filip Radlinski, 2011 .

Measuring Recommendation Explanation Quality: The Conflicting Goals of Explanations

Filip Radlinski, Krisztian Balog, Filip Radlinski, 2020, SIGIR.

Choices and constraints: research goals and approaches in information retrieval (part 2)

Filip Radlinski, Jaime Teevan, Diane Kelly, 2014, SIGIR.

Building A Personalized Tourist Attraction Recommender Sy stem Using Crowdsourcing (Demonstration)

Filip Radlinski, Ely Porat, Peter Key, 2014 .

Evaluating Search Engine Relevance with Click-Based Metrics

Filip Radlinski, Thorsten Joachims, Madhu Kurup, 2010, Preference Learning.

Predicting Search Satisfaction Metrics with Interleaved Comparisons

Filip Radlinski, Katja Hofmann, Anne Schuth, 2015, SIGIR.

Optimizing relevance and revenue in ad search: a query substitution approach

Filip Radlinski, Andrei Z. Broder, Evgeniy Gabrilovich, 2008, SIGIR '08.

An Eye-tracking Study of User Interactions with Query Auto Completion

Bhaskar Mitra, Milad Shokouhi, Filip Radlinski, 2014, CIKM.

On caption bias in interleaving experiments

Filip Radlinski, Katja Hofmann, Fritz Behr, 2012, CIKM '12.

Redundancy, diversity and interdependent document relevance

Filip Radlinski, Ben Carterette, Thorsten Joachims, 2009, SIGF.

Ranked bandits in metric spaces: learning diverse rankings over large document collections

Filip Radlinski, Sreenivas Gollapudi, Aleksandrs Slivkins, 2013, J. Mach. Learn. Res..

Learning optimally diverse rankings over large document collections

Filip Radlinski, Sreenivas Gollapudi, Aleksandrs Slivkins, 2010, ICML.

Practical Online Retrieval Evaluation

Filip Radlinski, Katja Hofmann, Filip Radlinski, 2013, ECIR.

Optimized interleaving for online retrieval evaluation

Filip Radlinski, Nick Craswell, Filip Radlinski, 2013, WSDM.

Search Engines that Learn from Implicit Feedback

Filip Radlinski, Thorsten Joachims, T. Joachims, 2007, Computer.

Coached Conversational Preference Elicitation: A Case Study in Understanding Movie Preferences

Filip Radlinski, Krisztian Balog, Bill Byrne, 2019, SIGdial.

Practical online retrieval evaluation

Filip Radlinski, Yisong Yue, Yisong Yue, 2011, SIGIR.

Preference elicitation as an optimization problem

Filip Radlinski, M. de Rijke, Maarten de Rijke, 2018, RecSys.

Filip Radlinski, Thorsten Joachims, Stefan Pohl, 2007, JCDL '07.

Evaluating the Robustness of Learning from Implicit Feedback pdf

Filip Radlinski, Thorsten Joachims, T. Joachims, 2006, ArXiv.

Detecting duplicate web documents using clickthrough data

Filip Radlinski, Paul N. Bennett, Emine Yilmaz, 2011, WSDM '11.

Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, San Francisco, CA, USA, February 22-25, 2016

Filip Radlinski, Paul N. Bennett, Jennifer Neville, 2016, WSDM.

CAIR'17: First International Workshop on Conversational Approaches to Information Retrieval at SIGIR 2017

Milad Shokouhi, Filip Radlinski, Hideo Joho, 2017, SIGIR Forum.

How does clickthrough data reflect retrieval quality?

Filip Radlinski, Thorsten Joachims, Madhu Kurup, 2008, CIKM '08.

A Theoretical Framework for Conversational Search

Filip Radlinski, Nick Craswell, Filip Radlinski, 2017, CHIIR.

On correlation of absence time and search effectiveness

Milad Shokouhi, Filip Radlinski, Sunandan Chakraborty, 2014, SIGIR.

Redundancy, Diversity, and Interdependent Document Relevance, a summary of the SIGIR 2009 workshop

Filip Radlinski, Ben Carterette, Paul N. Bennett, 2009 .

Embedding Search into a Conversational Platform to Support Collaborative Search

Filip Radlinski, Robert G. Capra, Jaime Arguello, 2019, CHIIR.

TREC Complex Answer Retrieval Overview

Filip Radlinski, Nick Craswell, Manisha Verma, 2018, TREC.

Relevance and Effort: An Analysis of Document Utility

Filip Radlinski, Peter Bailey, Emine Yilmaz, 2014, CIKM.

Learning diverse rankings with multi-armed bandits

Filip Radlinski, Thorsten Joachims, Robert D. Kleinberg, 2008, ICML '08.

Personalizing web search using long term browsing history

Filip Radlinski, Nicolaas Matthijs, Filip Radlinski, 2011, WSDM '11.

Comparing the sensitivity of information retrieval metrics

Filip Radlinski, Nick Craswell, Filip Radlinski, 2010, SIGIR.

Inferring query intent from reformulations and clicks

Filip Radlinski, Nick Craswell, Martin Szummer, 2010, WWW '10.

Evaluating the accuracy of implicit feedback from clicks and query reformulations in Web search

Filip Radlinski, Thorsten Joachims, Bing Pan, 2007, TOIS.

Learning Asymmetric Co-Relevance

Milad Shokouhi, Filip Radlinski, Oren Kurland, 2015, ICTIR.

Building a personalized tourist attraction recommender system using crowdsourcing

Filip Radlinski, Ely Porat, Yoram Bachrach, 2014, AAMAS.

Minimally Invasive Randomization for Collecting Unbiased Preferences from Clickthrough Logs

Filip Radlinski, Thorsten Joachims, T. Joachims, 2006, AAAI 2006.

Second International Workshop on Conversational Approaches to Information Retrieval (CAIR'18): Workshop at SIGIR 2018

Filip Radlinski, Hideo Joho, Jaime Arguello, 2018, SIGIR.

Towards Conversational Recommender Systems

Filip Radlinski, Katja Hofmann, Konstantina Christakopoulou, 2016, KDD.

Choices and constraints: research goals and approaches in information retrieval (part 1)

Filip Radlinski, Jaime Teevan, Diane Kelly, 2014, SIGIR.

Large-scale validation and analysis of interleaved search evaluation

Filip Radlinski, Thorsten Joachims, Yisong Yue, 2012, TOIS.

A support vector method for optimizing average precision

Filip Radlinski, Thorsten Joachims, Yisong Yue, 2007, SIGIR.

Metrics for assessing sets of subtopics

Filip Radlinski, Nick Craswell, Martin Szummer, 2010, SIGIR '10.

“I’D Rather Just Go to Bed”: Understanding Indirect Answers pdf

Filip Radlinski, Annie Louis, Dan Roth, 2020, EMNLP.

CAIR'18: Second International Workshop on Conversational Approaches to Information Retrieval at SIGIR 2018

Filip Radlinski, Hideo Joho, Jaime Arguello, 2019, SIGF.

Mortal Multi-Armed Bandits

Filip Radlinski, Eli Upfal, Deepayan Chakrabarti, 2008, NIPS.

Improving personalized web search using result diversification

Filip Radlinski, Susan T. Dumais, S. Dumais, 2006, SIGIR.

Understanding and Modeling Success in Email Search

Filip Radlinski, Susan T. Dumais, Fang Liu, 2017, SIGIR.

Diverse User Preference Elicitation with Multi-Armed Bandits

Filip Radlinski, Javier Parapar, Filip Radlinski, 2021, WSDM.

Soliciting User Preferences in Conversational Recommender Systems via Usage-related Questions

Filip Radlinski, Krisztian Balog, Ivica Kostric, 2021, RecSys.

Towards Unified Metrics for Accuracy and Diversity for Recommender Systems

Filip Radlinski, Javier Parapar, Filip Radlinski, 2021, RecSys.

On Interpretation and Measurement of Soft Attributes for Recommendation

Filip Radlinski, Krisztian Balog, Alexandros Karatzoglou, 2021, SIGIR.

Addressing Malicious Noise in Clickthrough Data

Filip Radlinski, Filip Radlinski, 2007 .

Online Study Behavior of 100,000 Students Preparing for the SAT, ACT, and GRE

Filip Radlinski, Vincent H. Crespi, Eric Loken, 2004 .