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Filip Radlinski
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2020 – today
- 2024
- [j10]Ivica Kostric
, Krisztian Balog
Generating Usage-related Questions for Preference Elicitation in Conversational Recommender Systems. Trans. Recomm. Syst. 2(2): 12:1-12:24 (2024) - [i18]John Palowitch, Hamidreza Alvari, Mehran Kazemi, Tanvir Amin, Filip Radlinski:
SocialQuotes: Learning Contextual Roles of Social Media Quotes on the Web. CoRR abs/2407.16007 (2024) - [i17]Krisztian Balog, John Palowitch, Barbara Ikica, Filip Radlinski, Hamidreza Alvari, Mehdi Manshadi:
Towards Realistic Synthetic User-Generated Content: A Scaffolding Approach to Generating Online Discussions. CoRR abs/2408.08379 (2024) - 2023
- [j9]Hamed Zamani, Johanne R. Trippas
Conversational Information Seeking. Found. Trends Inf. Retr. 17(3-4): 244-456 (2023) - [c59]Mohammad Javad Hosseini, Filip Radlinski, Silvia Pareti, Annie Louis:
Resolving Indirect Referring Expressions for Entity Selection. ACL (1) 2023: 12313-12335 - [c58]Krisztian Balog
Measuring the Impact of Explanation Bias: A Study of Natural Language Justifications for Recommender Systems. CHI Extended Abstracts 2023: 203:1-203:8 - [c57]Scott Sanner
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences. RecSys 2023: 890-896 - [c56]Arun Tejasvi Chaganty
Beyond Single Items: Exploring User Preferences in Item Sets with the Conversational Playlist Curation Dataset. SIGIR 2023: 2754-2764 - [c55]Valeria Fionda
Tutorials at The Web Conference 2023. WWW (Companion Volume) 2023: 648-658 - [i16]Megan Leszczynski, Ravi Ganti, Shu Zhang, Krisztian Balog, Filip Radlinski, Fernando Pereira, Arun Tejasvi Chaganty:
Generating Synthetic Data for Conversational Music Recommendation Using Random Walks and Language Models. CoRR abs/2301.11489 (2023) - [i15]Arun Tejasvi Chaganty, Megan Leszczynski, Shu Zhang, Ravi Ganti, Krisztian Balog, Filip Radlinski:
Beyond Single Items: Exploring User Preferences in Item Sets with the Conversational Playlist Curation Dataset. CoRR abs/2303.06791 (2023) - [i14]Krisztian Balog, Filip Radlinski, Andrey Petrov:
Measuring the Impact of Explanation Bias: A Study of Natural Language Justifications for Recommender Systems. CoRR abs/2303.09498 (2023) - [i13]Scott Sanner, Krisztian Balog, Filip Radlinski, Ben Wedin, Lucas Dixon:
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences. CoRR abs/2307.14225 (2023) - 2022
- [c54]Filip Radlinski, Craig Boutilier, Deepak Ramachandran, Ivan Vendrov:
Subjective Attributes in Conversational Recommendation Systems: Challenges and Opportunities. AAAI 2022: 12287-12293 - [c53]Filip Radlinski, Krisztian Balog, Fernando Diaz, Lucas Dixon, Ben Wedin:
On Natural Language User Profiles for Transparent and Scrutable Recommendation. SIGIR 2022: 2863-2874 - [c52]Jeffrey Dalton, Sophie Fischer, Paul Owoicho, Filip Radlinski, Federico Rossetto, Johanne R. Trippas
Conversational Information Seeking: Theory and Application. SIGIR 2022: 3455-3458 - [i12]Hamed Zamani, Johanne R. Trippas
Conversational Information Seeking. CoRR abs/2201.08808 (2022) - [i11]Filip Radlinski, Krisztian Balog, Fernando Diaz, Lucas Dixon, Ben Wedin:
On Natural Language User Profiles for Transparent and Scrutable Recommendation. CoRR abs/2205.09403 (2022) - [i10]Mohammad Javad Hosseini, Filip Radlinski, Silvia Pareti, Annie Louis:
Resolving Indirect Referring Expressions for Entity Selection. CoRR abs/2212.10933 (2022) - 2021
- [c51]Preksha Nema, Alexandros Karatzoglou, Filip Radlinski:
Disentangling Preference Representations for Recommendation Critiquing with ß-VAE. CIKM 2021: 1356-1365 - [c50]Javier Parapar, Filip Radlinski:
Towards Unified Metrics for Accuracy and Diversity for Recommender Systems. RecSys 2021: 75-84 - [c49]Ivica Kostric, Krisztian Balog, Filip Radlinski:
Soliciting User Preferences in Conversational Recommender Systems via Usage-related Questions. RecSys 2021: 724-729 - [c48]Krisztian Balog, Filip Radlinski, Alexandros Karatzoglou:
On Interpretation and Measurement of Soft Attributes for Recommendation. SIGIR 2021: 890-899 - [c47]Javier Parapar, Filip Radlinski:
Diverse User Preference Elicitation with Multi-Armed Bandits. WSDM 2021: 130-138 - [i9]Krisztian Balog, Filip Radlinski, Alexandros Karatzoglou:
On Interpretation and Measurement of Soft Attributes for Recommendation. CoRR abs/2105.09179 (2021) - [i8]Ivica Kostric, Krisztian Balog, Filip Radlinski:
Soliciting User Preferences in Conversational Recommender Systems via Usage-related Questions. CoRR abs/2111.13463 (2021) - 2020
- [c46]Annie Louis, Dan Roth, Filip Radlinski:
"I'd rather just go to bed": Understanding Indirect Answers. EMNLP (1) 2020: 7411-7425 - [c45]Krisztian Balog, Filip Radlinski:
Measuring Recommendation Explanation Quality: The Conflicting Goals of Explanations. SIGIR 2020: 329-338 - [i7]Krisztian Balog, Lucie Flekova, Matthias Hagen, Rosie Jones, Martin Potthast, Filip Radlinski, Mark Sanderson, Svitlana Vakulenko, Hamed Zamani:
Common Conversational Community Prototype: Scholarly Conversational Assistant. CoRR abs/2001.06910 (2020) - [i6]Annie Louis, Dan Roth, Filip Radlinski:
"I'd rather just go to bed": Understanding Indirect Answers. CoRR abs/2010.03450 (2020)
2010 – 2019
- 2019
- [c44]Sandeep Avula, Jaime Arguello, Robert Capra
Embedding Search into a Conversational Platform to Support Collaborative Search. CHIIR 2019: 15-23 - [c43]Filip Radlinski, Krisztian Balog, Bill Byrne, Karthik Krishnamoorthi:
Coached Conversational Preference Elicitation: A Case Study in Understanding Movie Preferences. SIGdial 2019: 353-360 - [c42]Krisztian Balog, Filip Radlinski, Shushan Arakelyan:
Transparent, Scrutable and Explainable User Models for Personalized Recommendation. SIGIR 2019: 265-274 - 2018
- [j8]Damiano Spina
CAIR'18: Second International Workshop on Conversational Approaches to Information Retrieval at SIGIR 2018. SIGIR Forum 52(2): 111-116 (2018) - [c41]Anna Sepliarskaia, Julia Kiseleva, Filip Radlinski, Maarten de Rijke
Preference elicitation as an optimization problem. RecSys 2018: 172-180 - [c40]Jaime Arguello, Filip Radlinski, Hideo Joho, Damiano Spina
Second International Workshop on Conversational Approaches to Information Retrieval (CAIR'18): Workshop at SIGIR 2018. SIGIR 2018: 1435-1437 - 2017
- [j7]Hideo Joho, Lawrence Cavedon
CAIR'17: First International Workshop on Conversational Approaches to Information Retrieval at SIGIR 2017. SIGIR Forum 51(3): 114-121 (2017) - [c39]Filip Radlinski, Nick Craswell:
A Theoretical Framework for Conversational Search. CHIIR 2017: 117-126 - [c38]Anna Sepliarskaia, Filip Radlinski, Maarten de Rijke:
Simple Personalized Search Based on Long-Term Behavioral Signals. ECIR 2017: 95-107 - [c37]Jin Young Kim, Nick Craswell, Susan T. Dumais, Filip Radlinski, Fang Liu:
Understanding and Modeling Success in Email Search. SIGIR 2017: 265-274 - [c36]Hideo Joho, Lawrence Cavedon
First International Workshop on Conversational Approaches to Information Retrieval (CAIR'17). SIGIR 2017: 1423-1424 - [c35]Laura Dietz
TREC Complex Answer Retrieval Overview. TREC 2017 - 2016
- [j6]Katja Hofmann, Lihong Li, Filip Radlinski:
Online Evaluation for Information Retrieval. Found. Trends Inf. Retr. 10(1): 1-117 (2016) - [c34]Konstantina Christakopoulou, Filip Radlinski, Katja Hofmann:
Towards Conversational Recommender Systems. KDD 2016: 815-824 - [c33]Sandro Bauer, Filip Radlinski, Ryen W. White:
Where Can I Buy a Boulder?: Searching for Offline Retail Locations. WWW 2016: 1225-1235 - [e1]Paul N. Bennett, Vanja Josifovski, Jennifer Neville, Filip Radlinski:
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, San Francisco, CA, USA, February 22-25, 2016. ACM 2016, ISBN 978-1-4503-3716-8 [contents] - 2015
- [c32]Fiana Raiber, Oren Kurland, Filip Radlinski, Milad Shokouhi:
Learning Asymmetric Co-Relevance. ICTIR 2015: 281-290 - [c31]Anne Schuth, Katja Hofmann, Filip Radlinski:
Predicting Search Satisfaction Metrics with Interleaved Comparisons. SIGIR 2015: 463-472 - [c30]Filip Radlinski:
Online Search Evaluation with Interleaving. WWW (Companion Volume) 2015: 917 - 2014
- [c29]Yoram Bachrach, Sofia Ceppi, Ian A. Kash, Peter B. Key, Filip Radlinski, Ely Porat, Michael Armstrong, Vijay Sharma:
Building a personalized tourist attraction recommender system using crowdsourcing. AAMAS 2014: 1631-1632 - [c28]Emine Yilmaz, Manisha Verma, Nick Craswell, Filip Radlinski, Peter Bailey:
Relevance and Effort: An Analysis of Document Utility. CIKM 2014: 91-100 - [c27]Katja Hofmann, Bhaskar Mitra, Filip Radlinski, Milad Shokouhi:
An Eye-tracking Study of User Interactions with Query Auto Completion. CIKM 2014: 549-558 - [c26]Bhaskar Mitra, Milad Shokouhi, Filip Radlinski, Katja Hofmann:
On user interactions with query auto-completion. SIGIR 2014: 1055-1058 - [c25]Sunandan Chakraborty, Filip Radlinski, Milad Shokouhi, Paul Baecke:
On correlation of absence time and search effectiveness. SIGIR 2014: 1163-1166 - [c24]Diane Kelly, Filip Radlinski, Jaime Teevan:
Choices and constraints: research goals and approaches in information retrieval (part 1). SIGIR 2014: 1283 - [c23]Diane Kelly, Filip Radlinski, Jaime Teevan:
Choices and constraints: research goals and approaches in information retrieval (part 2). SIGIR 2014: 1284 - 2013
- [j5]Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi:
Ranked bandits in metric spaces: learning diverse rankings over large document collections. J. Mach. Learn. Res. 14(1): 399-436 (2013) - [c22]Filip Radlinski, Katja Hofmann:
Practical Online Retrieval Evaluation. ECIR 2013: 878-881 - [c21]Milad Shokouhi, Ryen W. White, Paul N. Bennett, Filip Radlinski:
Fighting search engine amnesia: reranking repeated results. SIGIR 2013: 273-282 - [c20]Filip Radlinski, Nick Craswell:
Optimized interleaving for online retrieval evaluation. WSDM 2013: 245-254 - 2012
- [j4]Olivier Chapelle, Thorsten Joachims, Filip Radlinski, Yisong Yue:
Large-scale validation and analysis of interleaved search evaluation. ACM Trans. Inf. Syst. 30(1): 6:1-6:41 (2012) - [c19]Katja Hofmann, Fritz Behr, Filip Radlinski:
On caption bias in interleaving experiments. CIKM 2012: 115-124 - 2011
- [c18]Paul N. Bennett, Filip Radlinski, Ryen W. White, Emine Yilmaz:
Inferring and using location metadata to personalize web search. SIGIR 2011: 135-144 - [c17]Filip Radlinski, Yisong Yue:
Practical online retrieval evaluation. SIGIR 2011: 1301-1302 - [c16]Nicolaas Matthijs, Filip Radlinski:
Personalizing web search using long term browsing history. WSDM 2011: 25-34 - [c15]Filip Radlinski, Paul N. Bennett, Emine Yilmaz:
Detecting duplicate web documents using clickthrough data. WSDM 2011: 147-156 - 2010
- [c14]Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi:
Learning optimally diverse rankings over large document collections. ICML 2010: 983-990 - [c13]Filip Radlinski, Nick Craswell:
Comparing the sensitivity of information retrieval metrics. SIGIR 2010: 667-674 - [c12]Filip Radlinski, Martin Szummer, Nick Craswell:
Metrics for assessing sets of subtopics. SIGIR 2010: 853-854 - [c11]Filip Radlinski, Martin Szummer, Nick Craswell:
Inferring query intent from reformulations and clicks. WWW 2010: 1171-1172 - [p1]Filip Radlinski, Madhu Kurup, Thorsten Joachims:
Evaluating Search Engine Relevance with Click-Based Metrics. Preference Learning 2010: 337-361 - [i5]Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi:
Learning optimally diverse rankings over large document collections. CoRR abs/1005.5197 (2010)
2000 – 2009
- 2009
- [j3]Filip Radlinski, Paul N. Bennett, Ben Carterette, Thorsten Joachims:
Redundancy, diversity and interdependent document relevance. SIGIR Forum 43(2): 46-52 (2009) - 2008
- [b1]Filip Radlinski:
Learning to rank from implicit feedback. Cornell University, USA, 2008 - [c10]Filip Radlinski, Madhu Kurup, Thorsten Joachims:
How does clickthrough data reflect retrieval quality? CIKM 2008: 43-52 - [c9]Filip Radlinski, Robert Kleinberg, Thorsten Joachims:
Learning diverse rankings with multi-armed bandits. ICML 2008: 784-791 - [c8]Deepayan Chakrabarti, Ravi Kumar, Filip Radlinski, Eli Upfal:
Mortal Multi-Armed Bandits. NIPS 2008: 273-280 - [c7]Filip Radlinski, Andrei Z. Broder, Peter Ciccolo, Evgeniy Gabrilovich
Optimizing relevance and revenue in ad search: a query substitution approach. SIGIR 2008: 403-410 - 2007
- [j2]Thorsten Joachims, Filip Radlinski:
Search Engines that Learn from Implicit Feedback. Computer 40(8): 34-40 (2007) - [j1]Thorsten Joachims, Laura A. Granka, Bing Pan
Evaluating the accuracy of implicit feedback from clicks and query reformulations in Web search. ACM Trans. Inf. Syst. 25(2): 7 (2007) - [c6]Stefan Pohl, Filip Radlinski, Thorsten Joachims:
Recommending related papers based on digital library access records. JCDL 2007: 417-418 - [c5]Filip Radlinski, Thorsten Joachims:
Active exploration for learning rankings from clickthrough data. KDD 2007: 570-579 - [c4]Yisong Yue, Thomas Finley, Filip Radlinski, Thorsten Joachims:
A support vector method for optimizing average precision. SIGIR 2007: 271-278 - [i4]Stefan Pohl, Filip Radlinski, Thorsten Joachims:
Recommending Related Papers Based on Digital Library Access Records. CoRR abs/0704.2902 (2007) - 2006
- [c3]Filip Radlinski, Thorsten Joachims:
Minimally Invasive Randomization fro Collecting Unbiased Preferences from Clickthrough Logs. AAAI 2006: 1406-1412 - [c2]Filip Radlinski, Susan T. Dumais:
Improving personalized web search using result diversification. SIGIR 2006: 691-692 - [i3]Filip Radlinski, Thorsten Joachims:
Query Chains: Learning to Rank from Implicit Feedback. CoRR abs/cs/0605035 (2006) - [i2]Filip Radlinski, Thorsten Joachims:
Evaluating the Robustness of Learning from Implicit Feedback. CoRR abs/cs/0605036 (2006) - [i1]Filip Radlinski, Thorsten Joachims:
Minimally Invasive Randomization for Collecting Unbiased Preferences from Clickthrough Logs. CoRR abs/cs/0605037 (2006) - 2005
- [c1]Filip Radlinski, Thorsten Joachims:
Query chains: learning to rank from implicit feedback. KDD 2005: 239-248
Coauthor Index
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last updated on 2024-10-07 21:21 CEST by the dblp team
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