Category: Publications (page 1 of 9)

New publications

New publications that are scheduled to appear this month:

  • Mozhdeh Ariannezhad, Sebastian Schelter, and Maarten de Rijke. Demand Forecasting in the Presence of Privileged Information. In AALTD 2020: Workshop on Advanced Analytics and Learning on Temporal Data. Springer, September 2020. Bibtex, PDF
    @inproceedings{ariannezhad-2020-demand,
    Author = {Ariannezhad, Mozhdeh and Schelter, Sebastian and de Rijke, Maarten},
    Booktitle = {AALTD 2020: Workshop on Advanced Analytics and Learning on Temporal Data},
    Date-Added = {2020-07-16 18:11:34 +0200},
    Date-Modified = {2020-07-16 22:07:07 +0200},
    Month = {September},
    Publisher = {Springer},
    Title = {Demand Forecasting in the Presence of Privileged Information},
    Year = {2020}}
  • Jin Huang, Harrie Oosterhuis, Maarten de Rijke, and Herke van Hoof. Keeping Dataset Biases out of the Simulation: A Debiased Simulator for Reinforcement Learning based Recommender Systems. In RecSys 2020: The ACM Conference on Recommender Systems, page 190–199. ACM, September 2020. Bibtex, PDF
    @inproceedings{huang-2020-keeping,
    Author = {Huang, Jin and Oosterhuis, Harrie and de Rijke, Maarten and van Hoof, Herke},
    Booktitle = {RecSys 2020: The ACM Conference on Recommender Systems},
    Date-Added = {2020-07-23 08:03:19 +0200},
    Date-Modified = {2020-09-19 09:47:04 +0200},
    Month = {September},
    Pages = {190--199},
    Publisher = {ACM},
    Title = {Keeping Dataset Biases out of the Simulation: A Debiased Simulator for Reinforcement Learning based Recommender Systems},
    Year = {2020}}
  • Chang Li, Haoyun Feng, and Maarten de Rijke. Cascading Hybrid Bandits: Online Learning to Rank for Relevance and Diversity. In RecSys 2020: The ACM Conference on Recommender Systems, page 33–42. ACM, September 2020. Bibtex, PDF
    @inproceedings{li-2020-cascading,
    Author = {Li, Chang and Feng, Haoyun and de Rijke, Maarten},
    Booktitle = {RecSys 2020: The ACM Conference on Recommender Systems},
    Date-Added = {2020-07-23 07:41:55 +0200},
    Date-Modified = {2020-09-19 09:46:34 +0200},
    Month = {September},
    Pages = {33--42},
    Publisher = {ACM},
    Title = {Cascading Hybrid Bandits: Online Learning to Rank for Relevance and Diversity},
    Year = {2020}}
  • Harrie Oosterhuis and Maarten de Rijke. Taking the Counterfactual Online: Efficient and Unbiased Online Evaluation for Ranking. In ICTIR 2020: The 6th ACM International Conference on the Theory of Information Retrieval, page 137–144. ACM, September 2020. Bibtex, PDF
    @inproceedings{oosterhuis-2020-taking,
    Author = {Oosterhuis, Harrie and de Rijke, Maarten},
    Booktitle = {ICTIR 2020: The 6th ACM International Conference on the Theory of Information Retrieval},
    Date-Added = {2020-06-30 10:31:31 +0200},
    Date-Modified = {2020-09-15 06:54:46 +0200},
    Month = {September},
    Pages = {137--144},
    Publisher = {ACM},
    Title = {Taking the Counterfactual Online: Efficient and Unbiased Online Evaluation for Ranking},
    Year = {2020}}
  • Chuan Wu, Evangelos Kanoulas, and Maarten de Rijke. It All Starts with Entities: A Salient Entity Topic Model. Natural Language Engineering, 26(5):531–549, September 2020. Bibtex, PDF
    @article{wu-2020-all,
    Author = {Wu, Chuan and Kanoulas, Evangelos and de Rijke, Maarten},
    Date-Added = {2018-09-21 10:00:04 +0200},
    Date-Modified = {2020-08-12 06:43:39 +0200},
    Journal = {Natural Language Engineering},
    Month = {September},
    Number = {5},
    Pages = {531--549},
    Title = {It All Starts with Entities: A Salient Entity Topic Model},
    Volume = {26},
    Year = {2020}}

New publications

Some new papers that are scheduled to appear this month:

  • Zeynep Akata, Dan Balliet, Maarten de Rijke, Frank Dignum, Virginia Dignum, Guszti Eiben, Antske Fokkens, Davide Grossi, Koen Hindriks, Holger Hoos, Haley Hung, Catholijn Jonker, Christof Monz, Mark Neerincx, Frans Oliehoek, Henri Prakken, Stefan Schlobach, Linda van der Gaag, Frank van Harmelen, Herke van Hoof, Birna van Riemsdijk, Aimee van Wynsberghe, Rineke Verbrugge, Bart Verheij, Piek Vossen, and Max Welling. A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer, 53(08):18-28, August 2020. Bibtex, PDF
    @article{akata-2020-research,
    Author = {Akata, Zeynep and Balliet, Dan and de Rijke, Maarten and Dignum, Frank and Dignum, Virginia and Eiben, Guszti and Fokkens, Antske and Grossi, Davide and Hindriks, Koen and Hoos, Holger and Hung, Haley and Jonker, Catholijn and Monz, Christof and Neerincx, Mark and Oliehoek, Frans and Prakken, Henri and Schlobach, Stefan and van der Gaag, Linda and van Harmelen, Frank and van Hoof, Herke and van Riemsdijk, Birna and van Wynsberghe, Aimee and Verbrugge, Rineke and Verheij, Bart and Vossen, Piek and Welling, Max},
    Date-Added = {2020-08-11 21:26:55 +0200},
    Date-Modified = {2020-08-11 21:30:19 +0200},
    Journal = {Computer},
    Month = {August},
    Number = {08},
    Pages = {18-28},
    Title = {A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence},
    Volume = {53},
    Year = {2020},
    Bdsk-Url-1 = {https://doi.org/10.1109/MC.2020.2996587}}
  • Yifan Chen, Yang Wang, Xiang Zhao, Jie Zou, and Maarten de Rijke. Block-aware Item Similarity Models for Top-$N$ Recommendation. ACM Transactions on Information Systems, 38(4):Article 42, September 2020. Bibtex, PDF
    @article{chen-2020-block-aware,
    Author = {Chen, Yifan and Wang, Yang and Zhao, Xiang and Zou, Jie and de Rijke, Maarten},
    Date-Added = {2019-12-07 08:29:15 +0100},
    Date-Modified = {2020-09-11 07:41:45 +0200},
    Journal = {ACM Transactions on Information Systems},
    Month = {September},
    Number = {4},
    Pages = {Article 42},
    Title = {Block-aware Item Similarity Models for Top-$N$ Recommendation},
    Volume = {38},
    Year = {2020}}
  • Chang Li, Ilya Markov, Maarten de Rijke, and Masrour Zoghi. MergeDTS: A Method for Effective Large-scale Online Ranker Evaluation. ACM Transactions on Information Systems, 38(4):Article 40, September 2020. Bibtex, PDF
    @article{li-2020-mergedts,
    Author = {Li, Chang and Markov, Ilya and de Rijke, Maarten and Zoghi, Masrour},
    Date-Added = {2018-12-01 09:14:01 +0100},
    Date-Modified = {2020-09-11 07:42:03 +0200},
    Journal = {ACM Transactions on Information Systems},
    Month = {September},
    Number = {4},
    Pages = {Article 40},
    Title = {MergeDTS: A Method for Effective Large-scale Online Ranker Evaluation},
    Volume = {38},
    Year = {2020}}
  • Yujie Lin, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Jun Ma, and Maarten de Rijke. Explainable Fashion Recommendation with Joint Outfit Matching and Comment Generation. IEEE Transactions on Knowledge and Data Engineering, 32(8):1502–1516, August 2020. Bibtex, PDF
    @article{lin-2020-explainable,
    Author = {Lin, Yujie and Ren, Pengjie and Chen, Zhumin and Ren, Zhaochun and Ma, Jun and de Rijke, Maarten},
    Date-Added = {2018-06-19 19:07:42 +0000},
    Date-Modified = {2020-07-09 07:23:00 +0200},
    Journal = {IEEE Transactions on Knowledge and Data Engineering},
    Month = {August},
    Number = {8},
    Pages = {1502--1516},
    Title = {Explainable Fashion Recommendation with Joint Outfit Matching and Comment Generation},
    Volume = {32},
    Year = {2020}}

New publications

It’s July, it’s the month of SIGIR, so several publications will come out this month:

  • Mariya Hendriksen, Ernst Kuiper, Pim Nauts, Sebastian Schelter, and Maarten de Rijke. Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers. In eCOM 2020: The 2020 SIGIIR Workshop on eCommerce. ACM, July 2020. Bibtex, PDF
    @inproceedings{hendriksen-2020-analyzing,
    Author = {Hendriksen, Mariya and Kuiper, Ernst and Nauts, Pim and Schelter, Sebastian and de Rijke, Maarten},
    Booktitle = {eCOM 2020: The 2020 SIGIIR Workshop on eCommerce},
    Date-Added = {2020-07-13 05:40:42 +0200},
    Date-Modified = {2020-07-13 05:42:59 +0200},
    Month = {July},
    Publisher = {ACM},
    Title = {Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers},
    Year = {2020}}
  • Rolf Jagerman and Maarten de Rijke. Accelerated Convergence for Counterfactual Learning to Rank. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval, page 469–478. ACM, July 2020. Bibtex, PDF
    @inproceedings{jagerman-2020-accelerated,
    Author = {Jagerman, Rolf and de Rijke, Maarten},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 08:49:46 +0200},
    Date-Modified = {2020-08-13 19:33:41 +0200},
    Month = {July},
    Pages = {469--478},
    Publisher = {ACM},
    Title = {Accelerated Convergence for Counterfactual Learning to Rank},
    Year = {2020}}
  • Wenqiang Lei, Xiangnan He, Maarten de Rijke, and Tat-Seng Chua. Conversational Recommendation: Formulation, Methods, and Evaluation. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval. ACM, July 2020. Bibtex, PDF
    @inproceedings{lei-2020-conversational,
    Author = {Lei, Wenqiang and He, Xiangnan and de Rijke, Maarten and Chua, Tat-Seng},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 07:58:06 +0200},
    Date-Modified = {2020-04-23 07:59:15 +0200},
    Month = {July},
    Publisher = {ACM},
    Title = {Conversational Recommendation: Formulation, Methods, and Evaluation},
    Year = {2020}}
  • Yujie Lin, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Dongxiao Yu, Jun Ma, Maarten de Rijke, and Xiuzhen Cheng. Meta Matrix Factorization for Federated Rating Predictions. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval, page 981–990. ACM, July 2020. Bibtex, PDF
    @inproceedings{lin-2020-meta,
    Author = {Lin, Yujie and Ren, Pengjie and Chen, Zhumin and Ren, Zhaochun and Yu, Dongxiao and Ma, Jun and de Rijke, Maarten and Cheng, Xiuzhen},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 08:51:36 +0200},
    Date-Modified = {2020-08-13 19:34:46 +0200},
    Month = {July},
    Pages = {981--990},
    Publisher = {ACM},
    Title = {Meta Matrix Factorization for Federated Rating Predictions},
    Year = {2020}}
  • Chuan Meng, Pengjie Ren, Zhumin Chen, Weiwei Sun, Zhaochun Ren, Zhaopeng Tu, and Maarten de Rijke. DukeNet: A Dual Knowledge Interaction Network for Knowledge-Grounded Conversation. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval, page 1151–1160. ACM, July 2020. Bibtex, PDF
    @inproceedings{meng-2020-dukenet,
    Author = {Meng, Chuan and Ren, Pengjie and Chen, Zhumin and Sun, Weiwei and Ren, Zhaochun and Tu, Zhaopeng and de Rijke, Maarten},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 08:53:11 +0200},
    Date-Modified = {2020-08-13 19:35:05 +0200},
    Month = {July},
    Pages = {1151--1160},
    Publisher = {ACM},
    Title = {DukeNet: A Dual Knowledge Interaction Network for Knowledge-Grounded Conversation},
    Year = {2020}}
  • Harrie Oosterhuis and Maarten de Rijke. Policy-Aware Unbiased Learning to Rank for Top-k Rankings. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval, page 489–498. ACM, July 2020. Bibtex, PDF
    @inproceedings{oosterhuis-2020-policy-aware,
    Author = {Oosterhuis, Harrie and de Rijke, Maarten},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 21:52:52 +0200},
    Date-Modified = {2020-08-13 19:35:25 +0200},
    Month = {July},
    Pages = {489--498},
    Publisher = {ACM},
    Title = {Policy-Aware Unbiased Learning to Rank for Top-k Rankings},
    Year = {2020}}
  • Zhiqiang Pan, Fei Cai, Yanxiang Ling, and Maarten de Rijke. An Intent-guided Collaborative Machine for Session-based Recommendation. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval, page 1833–1836. ACM, July 2020. Bibtex, PDF
    @inproceedings{pan-2020-intent-guided,
    Author = {Pan, Zhiqiang and Cai, Fei and Ling, Yanxiang and de Rijke, Maarten},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 08:59:25 +0200},
    Date-Modified = {2020-08-13 19:36:13 +0200},
    Month = {July},
    Pages = {1833--1836},
    Publisher = {ACM},
    Title = {An Intent-guided Collaborative Machine for Session-based Recommendation},
    Year = {2020}}
  • Zhiqiang Pan, Fei Cai, Yanxiang Ling, and Maarten de Rijke. Rethinking Item Importance in Session-based Recommendation. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval, page 1837–1840. ACM, July 2020. Bibtex, PDF
    @inproceedings{pan-2020-rethinking,
    Author = {Pan, Zhiqiang and Cai, Fei and Ling, Yanxiang and de Rijke, Maarten},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 09:01:41 +0200},
    Date-Modified = {2020-08-13 19:35:50 +0200},
    Month = {July},
    Pages = {1837--1840},
    Publisher = {ACM},
    Title = {Rethinking Item Importance in Session-based Recommendation},
    Year = {2020}}
  • Fatemeh Sarvi, Nikos Voskarides, Lois Mooiman, Sebastian Schelter, and Maarten de Rijke. A Comparison of Supervised Learning to Match Methods for Product Search. In eCOM 2020: The 2020 SIGIIR Workshop on eCommerce. ACM, July 2020. Bibtex, PDF
    @inproceedings{sarvi-2020-comparison,
    Author = {Sarvi, Fatemeh and Voskarides, Nikos and Mooiman, Lois and Schelter, Sebastian and de Rijke, Maarten},
    Booktitle = {eCOM 2020: The 2020 SIGIIR Workshop on eCommerce},
    Date-Added = {2020-07-13 05:34:59 +0200},
    Date-Modified = {2020-07-13 05:39:22 +0200},
    Month = {July},
    Publisher = {ACM},
    Title = {A Comparison of Supervised Learning to Match Methods for Product Search},
    Year = {2020}}
  • Anton Steenvoorden, Emanuele Di Gloria, Wanyu Chen, Pengjie Ren, and Maarten de Rijke. Attribute-aware Diversification for Sequential Recommendations. In AIIS: The SIGIR 2020 Workshop on Applied Interactive Information Systems. ACM, July 2020. Bibtex, PDF
    @inproceedings{steenvoorden-2020-attribute-aware,
    Author = {Steenvoorden, Anton and Di Gloria, Emanuele and Chen, Wanyu and Ren, Pengjie and de Rijke, Maarten},
    Booktitle = {AIIS: The SIGIR 2020 Workshop on Applied Interactive Information Systems},
    Date-Added = {2020-06-13 22:17:48 +0200},
    Date-Modified = {2020-07-30 10:30:24 +0200},
    Month = {July},
    Publisher = {ACM},
    Title = {Attribute-aware Diversification for Sequential Recommendations},
    Year = {2020}}
  • Svitlana Vakulenko, Evangelos Kanoulas, and Maarten de Rijke. An Analysis of Mixed Initiative and Collaboration in Information-Seeking Dialogues. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval, page 2085–2088. ACM, July 2020. Bibtex, PDF
    @inproceedings{vakulenko-2020-analysis,
    Author = {Vakulenko, Svitlana and Kanoulas, Evangelos and de Rijke, Maarten},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 09:02:17 +0200},
    Date-Modified = {2020-08-13 19:37:55 +0200},
    Month = {July},
    Pages = {2085--2088},
    Publisher = {ACM},
    Title = {An Analysis of Mixed Initiative and Collaboration in Information-Seeking Dialogues},
    Year = {2020}}
  • Ali Vardasbi, Maarten de Rijke, and Ilya Markov. Cascade Model-based Propensity Estimation for Counterfactual Learning to Rank. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval, page 2089–2092. ACM, July 2020. Bibtex, PDF
    @inproceedings{vardasbi-2020-cascade,
    Author = {Vardasbi, Ali and de Rijke, Maarten and Markov, Ilya},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 09:27:55 +0200},
    Date-Modified = {2020-08-13 19:38:21 +0200},
    Month = {July},
    Pages = {2089--2092},
    Publisher = {ACM},
    Title = {Cascade Model-based Propensity Estimation for Counterfactual Learning to Rank},
    Year = {2020}}
  • Nikos Voskarides, Dan Li, Pengjie Ren, Evangelos Kanoulas, and Maarten de Rijke. Query Resolution for Conversational Search with Limited Supervision. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval, page 921–932. ACM, July 2020. Bibtex, PDF
    @inproceedings{voskarides-2020-query,
    Author = {Voskarides, Nikos and Li, Dan and Ren, Pengjie and Kanoulas, Evangelos and de Rijke, Maarten},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 09:29:00 +0200},
    Date-Modified = {2020-08-13 19:38:48 +0200},
    Month = {July},
    Pages = {921--932},
    Publisher = {ACM},
    Title = {Query Resolution for Conversational Search with Limited Supervision},
    Year = {2020}}
  • Shanshan Wang, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Jian-Yun Nie, Jun Ma, and Maarten de Rijke. Coding Electronic Health Records with Adversarial Reinforcement Path Generation. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval, page 801–810. ACM, July 2020. Bibtex, PDF
    @inproceedings{wang-2020-coding,
    Author = {Wang, Shanshan and Ren, Pengjie and Chen, Zhumin and Ren, Zhaochun and Nie, Jian-Yun and Ma, Jun and de Rijke, Maarten},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 09:33:42 +0200},
    Date-Modified = {2020-08-13 19:39:27 +0200},
    Month = {July},
    Pages = {801--810},
    Publisher = {ACM},
    Title = {Coding Electronic Health Records with Adversarial Reinforcement Path Generation},
    Year = {2020}}
  • Xiaohui Xie, Jiaxin Mao, Yiqun Liu, and Maarten de Rijke. Modeling User Behavior for Vertical Search: Images, Apps and Products. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval. ACM, July 2020. Bibtex, PDF
    @inproceedings{xie-2020-modeling,
    Author = {Xie, Xiaohui and Mao, Jiaxin and Liu, Yiqun and de Rijke, Maarten},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 07:54:32 +0200},
    Date-Modified = {2020-04-23 07:57:53 +0200},
    Month = {July},
    Publisher = {ACM},
    Title = {Modeling User Behavior for Vertical Search: Images, Apps and Products},
    Year = {2020}}
  • Xiaohui Xie, Jiaxin Mao, Yiqun Liu, Maarten de Rijke, Haitian Chen, Min Zhang, and Shaoping Ma. Preference-based Evaluation Metrics for Web Image Search. In SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval, page 369–378. ACM, July 2020. Bibtex, PDF
    @inproceedings{xie-2020-preference-based,
    Author = {Xie, Xiaohui and Mao, Jiaxin and Liu, Yiqun and de Rijke, Maarten and Chen, Haitian and Zhang, Min and Ma, Shaoping},
    Booktitle = {SIGIR 2020: 43rd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2020-04-23 09:30:19 +0200},
    Date-Modified = {2020-08-13 19:40:02 +0200},
    Month = {July},
    Pages = {369--378},
    Publisher = {ACM},
    Title = {Preference-based Evaluation Metrics for Web Image Search},
    Year = {2020}}

New publications

Some new papers that are scheduled to come out this month:

  • Maurits Bleeker and Maarten de Rijke. Bidirectional Scene Text Recognition with a Single Decoder. In 24th European Conference on Artificial Intelligence. IOS Press, June 2020. Bibtex, PDF
    @inproceedings{bleeker-2020-bidirectional,
    Author = {Bleeker, Maurits and de Rijke, Maarten},
    Booktitle = {24th European Conference on Artificial Intelligence},
    Date-Added = {2020-01-14 20:43:50 +0100},
    Date-Modified = {2020-01-14 20:45:45 +0100},
    Month = {June},
    Publisher = {IOS Press},
    Title = {Bidirectional Scene Text Recognition with a Single Decoder},
    Year = {2020}}
  • Wanyu Chen, Fei Cai, Honghui Chen, and Maarten de Rijke. Personalized Query Suggestion Diversification in Information Retrieval. Frontiers of Computer Science, 14(3), June 2020. Bibtex, PDF
    @article{chen-2020-personalized,
    Author = {Chen, Wanyu and Cai, Fei and Chen, Honghui and de Rijke, Maarten},
    Date-Added = {2017-08-13 04:36:27 +0000},
    Date-Modified = {2020-01-14 14:34:23 +0100},
    Journal = {Frontiers of Computer Science},
    Month = {June},
    Number = {3},
    Title = {Personalized Query Suggestion Diversification in Information Retrieval},
    Volume = {14},
    Year = {2020}}
  • Jiahuan Pei, Pengjie Ren, Christof Monz, and Maarten de Rijke. Retrospective and Prospective Mixture-of-Generators for Task-oriented Dialogue Response Generation. In 24th European Conference on Artificial Intelligence. IOS Press, June 2020. Bibtex, PDF
    @inproceedings{pei-2020-retrospective,
    Author = {Pei, Jiahuan and Ren, Pengjie and Monz, Christof and de Rijke, Maarten},
    Booktitle = {24th European Conference on Artificial Intelligence},
    Date-Added = {2020-01-14 20:45:49 +0100},
    Date-Modified = {2020-01-14 20:47:19 +0100},
    Month = {June},
    Publisher = {IOS Press},
    Title = {Retrospective and Prospective Mixture-of-Generators for Task-oriented Dialogue Response Generation},
    Year = {2020}}
  • Manos Tsagkias, Tracy Holloway King, Surya Kallumadi, Vanessa Murdock, and Maarten de Rijke. Challenges and Research Opportunities in eCommerce Search and Recommendations. SIGIR Forum, 54(1), June 2020. Bibtex, PDF
    @article{tsagkias-2020-challenges,
    Author = {Tsagkias, Manos and King, Tracy Holloway and Kallumadi, Surya and Murdock, Vanessa and de Rijke, Maarten},
    Date-Added = {2020-05-11 00:24:45 +0200},
    Date-Modified = {2020-05-11 00:30:51 +0200},
    Journal = {SIGIR Forum},
    Month = {June},
    Number = {1},
    Title = {Challenges and Research Opportunities in eCommerce Search and Recommendations},
    Volume = {54},
    Year = {2020}}

New publications

Some new papers that are scheduled to come out this month:

  • Rolf Jagerman, Ilya Markov, and Maarten de Rijke. Safe Exploration for Optimizing Contextual Bandits. ACM Transactions on Information Systems, 38(3):Article 24, June 2020. Bibtex, PDF
    @article{jagerman-2020-safe,
    Author = {Jagerman, Rolf and Markov, Ilya and de Rijke, Maarten},
    Date-Added = {2019-05-31 20:33:35 +0200},
    Date-Modified = {2020-09-11 07:43:02 +0200},
    Journal = {ACM Transactions on Information Systems},
    Month = {June},
    Number = {3},
    Pages = {Article 24},
    Title = {Safe Exploration for Optimizing Contextual Bandits},
    Volume = {38},
    Year = {2020}}
  • Chuan Wu, Evangelos Kanoulas, and Maarten de Rijke. Learning Entity-Centric Document Representations using an Entity Facet Topic Model. Information Processing & Management, 57(3), May 2020. Bibtex, PDF
    @article{wu-2020-learning,
    Author = {Wu, Chuan and Kanoulas, Evangelos and de Rijke, Maarten},
    Date-Added = {2018-09-30 08:12:13 +0200},
    Date-Modified = {2020-02-12 09:41:29 -0500},
    Journal = {Information Processing \& Management},
    Month = {May},
    Number = {3},
    Title = {Learning Entity-Centric Document Representations using an Entity Facet Topic Model},
    Volume = {57},
    Year = {2020}}
  • Chuan Wu, Evangelos Kanoulas, Maarten de Rijke, and Wei Lu. WN-Salience: A Corpus of News Articles with Entity Salience Annotations. In 12th International Conference on Language Resources and Evaluation, page 2088–2095. ELRA, May 2020. Bibtex, PDF
    @inproceedings{wu-2020-wn-salience,
    Author = {Wu, Chuan and Kanoulas, Evangelos and de Rijke, Maarten and Lu, Wei},
    Booktitle = {12th International Conference on Language Resources and Evaluation},
    Date-Added = {2020-02-12 04:49:47 -0500},
    Date-Modified = {2020-05-16 10:14:49 +0200},
    Month = {May},
    Pages = {2088--2095},
    Publisher = {ELRA},
    Title = {WN-Salience: A Corpus of News Articles with Entity Salience Annotations},
    Year = {2020}}

CIKM 2019 papers online

The papers that my team and I will be presenting at CIKM 2019 are online now:

  • Wanyu Chen, Fei Cai, Chen Honghui, and Maarten de Rijke. A Dynamic Co-attention Network for Session-based Recommendation. In CIKM 2019: 28th ACM Conference on Information and Knowledge Management, pages 1461-1470. ACM, November 2019. Bibtex, PDF
    @inproceedings{chen-2019-dynamic,
    Author = {Chen, Wanyu and Cai, Fei and Chen Honghui and de Rijke, Maarten},
    Booktitle = {CIKM 2019: 28th ACM Conference on Information and Knowledge Management},
    Date-Added = {2019-08-09 09:21:52 +0200},
    Date-Modified = {2019-11-05 18:09:20 +0800},
    Month = {November},
    Pages = {1461-1470},
    Publisher = {ACM},
    Title = {A Dynamic Co-attention Network for Session-based Recommendation},
    Year = {2019}}
  • Svitlana Vakulenko, Javier Fernández, Axel Polleres, Maarten de Rijke, and Michael Cochez. Message Passing for Complex Question Answering over Knowledge Graphs. In CIKM 2019: 28th ACM Conference on Information and Knowledge Management, page 1431–1440. ACM, November 2019. Bibtex, PDF
    @inproceedings{vakulenko-2019-message,
    Author = {Vakulenko, Svitlana and Fern{\'{a}}ndez, Javier and Polleres, Axel and de Rijke, Maarten and Cochez, Michael},
    Booktitle = {CIKM 2019: 28th ACM Conference on Information and Knowledge Management},
    Date-Added = {2019-08-09 09:27:58 +0200},
    Date-Modified = {2019-11-03 21:15:35 +0800},
    Month = {November},
    Pages = {1431--1440},
    Publisher = {ACM},
    Title = {Message Passing for Complex Question Answering over Knowledge Graphs},
    Year = {2019}}
  • Shanshan Wang, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Jun Ma, and Maarten de Rijke. Order-free Medicine Combination Prediction With Graph Convolutional Reinforcement Learning. In CIKM 2019: 28th ACM Conference on Information and Knowledge Management, page 1623–1632. ACM, November 2019. Bibtex, PDF
    @inproceedings{wang-2019-order-free,
    Author = {Wang, Shanshan and Ren, Pengjie and Chen, Zhumin and Ren, Zhaochun and Ma, Jun and de Rijke, Maarten},
    Booktitle = {CIKM 2019: 28th ACM Conference on Information and Knowledge Management},
    Date-Added = {2019-08-09 09:23:55 +0200},
    Date-Modified = {2019-11-03 21:16:13 +0800},
    Month = {November},
    Pages = {1623--1632},
    Publisher = {ACM},
    Title = {Order-free Medicine Combination Prediction With Graph Convolutional Reinforcement Learning},
    Year = {2019}}
  • Xiaohui Xie, Jiaxin Mao, Yiqun Liu, Maarten de Rijke, Qingyao Ai, Yufei Huang, Min Zhang, and Shaoping Ma. Improving Web Image Search with Contextual Information. In CIKM 2019: 28th ACM Conference on Information and Knowledge Management, page 1683–1692. ACM, November 2019. Bibtex, PDF
    @inproceedings{xie-2019-improving,
    Author = {Xie, Xiaohui and Mao, Jiaxin and Liu, Yiqun and de Rijke, Maarten and Ai, Qingyao and Huang, Yufei and Zhang, Min and Ma, Shaoping},
    Booktitle = {CIKM 2019: 28th ACM Conference on Information and Knowledge Management},
    Date-Added = {2019-08-09 09:26:32 +0200},
    Date-Modified = {2019-11-03 21:16:30 +0800},
    Month = {November},
    Pages = {1683--1692},
    Publisher = {ACM},
    Title = {Improving Web Image Search with Contextual Information},
    Year = {2019}}

IJCAI 2019 papers online

Cascading non-stationary bandits: Online learning to rank in the non-stationary cascade model by Chang Li and Maarten de Rijke is online now at this location.

In the paper, we argue that non-stationarity appears in many online applications such as web search and advertising. We study the online learning to rank problem in a non-stationary environment where user preferences change abruptly at an unknown moment in time. We consider the problem of identifying the K most attractive items and propose cascading non-stationary bandits, an online learning variant of the cascading model, where a user browses a ranked list from top to bottom and clicks on the first attractive item. We propose two algorithms for solving this non-stationary problem: CascadeDUCB andCascadeSWUCB. We analyze their performance and derive gap-dependent upper bounds on the $n$-step regret of these algorithms. We also establish a lower bound on the regret for cascading non-stationary bandits and show that both algorithms match the lower bound up to a logarithmic factor. Finally, we evaluate their performance on a real-world web search click dataset.

  • Chang Li and Maarten de Rijke. Cascading non-stationary bandits: Online learning to rank in the non-stationary cascade model. In IJCAI 2019: Twenty-Eighth International Joint Conference on Artificial Intelligence, page 2859–2865, August 2019. Bibtex, PDF
    @inproceedings{li-2019-cascading,
    Author = {Li, Chang and de Rijke, Maarten},
    Booktitle = {IJCAI 2019: Twenty-Eighth International Joint Conference on Artificial Intelligence},
    Date-Added = {2019-05-30 22:36:52 +0200},
    Date-Modified = {2019-08-04 15:53:45 +0200},
    Month = {August},
    Pages = {2859--2865},
    Title = {Cascading non-stationary bandits: Online learning to rank in the non-stationary cascade model},
    Year = {2019}}

Other papers and presentations at IJCAI are part of the SCAI workshop:

  • Jiahuan Pei, Arent Stienstra, Julia Kiseleva, and Maarten de Rijke. SEntNet: Source-aware Recurrent Entity Networks for Dialogue Response Selection. In 4th International Workshop on Search-Oriented Conversational AI (SCAI), August 2019. Bibtex, PDF
    @inproceedings{pei-2019-sentnet,
    Author = {Pei, Jiahuan and Stienstra, Arent and Kiseleva, Julia and de Rijke, Maarten},
    Booktitle = {4th International Workshop on Search-Oriented Conversational AI (SCAI)},
    Date-Added = {2019-06-06 11:55:06 +0200},
    Date-Modified = {2019-06-06 11:56:16 +0200},
    Month = {August},
    Title = {SEntNet: Source-aware Recurrent Entity Networks for Dialogue Response Selection},
    Year = {2019}}
  • Yangjun Zhang, Pengjie Ren, and Maarten de Rijke. Improving Background Based Conversation with Context-aware Knowledge Pre-selection. In 4th International Workshop on Search-Oriented Conversational AI (SCAI), August 2019. Bibtex, PDF
    @inproceedings{zhang-2019-improving,
    Author = {Zhang, Yangjun and Ren, Pengjie and de Rijke, Maarten},
    Booktitle = {4th International Workshop on Search-Oriented Conversational AI (SCAI)},
    Date-Added = {2019-06-06 11:53:36 +0200},
    Date-Modified = {2019-06-06 11:55:01 +0200},
    Month = {August},
    Title = {Improving Background Based Conversation with Context-aware Knowledge Pre-selection},
    Year = {2019}}

  • Maarten de Rijke and Pengjie Ren. SERP-based Conversations. In 4th International Workshop on Search-Oriented Conversational AI (SCAI), August 2019. 

SIGIR 2019 papers online

Here’s our harvest for SIGIR 2019, which is about to get started in less than 24 hours:

  • Joris Baan, Maartje ter Hoeve, Marlies van der Wees, Anne Schuth, and Maarten de Rijke. Do Transformer Attention Heads Provide Transparency in Abstractive Summarization?. In FACTS-IR: SIGIR 2019 Workshop on Fairness, Accountability, Confidentiality, Transparency and Safety in Information Retrieval, July 2019. Bibtex, PDF
    @inproceedings{baan-2019-do,
    Author = {Baan, Joris and ter Hoeve, Maartje and van der Wees, Marlies and Schuth, Anne and de Rijke, Maarten},
    Booktitle = {FACTS-IR: SIGIR 2019 Workshop on Fairness, Accountability, Confidentiality, Transparency and Safety in Information Retrieval},
    Date-Added = {2019-05-31 22:24:14 +0200},
    Date-Modified = {2019-05-31 22:38:02 +0200},
    Month = {July},
    Title = {Do Transformer Attention Heads Provide Transparency in Abstractive Summarization?},
    Year = {2019}}
  • Yifan Chen, Pengjie Ren, Yang Wang, and Maarten de Rijke. Bayesian Personalized Feature Interaction Selection for Factorization Machines. In SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval, page 665–674. ACM, July 2019. Bibtex, PDF
    @inproceedings{chen-2019-bayesian,
    Author = {Chen, Yifan and Ren, Pengjie and Wang, Yang and de Rijke, Maarten},
    Booktitle = {SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2019-04-14 16:48:31 +0200},
    Date-Modified = {2019-08-02 15:58:43 +0200},
    Month = {July},
    Pages = {665--674},
    Publisher = {ACM},
    Title = {Bayesian Personalized Feature Interaction Selection for Factorization Machines},
    Year = {2019}}
  • Yang Fang, Xiang Zhao, Peixin Huang, Weidong Xiao, and Maarten de Rijke. M-HIN: Complex Embeddings for Heterogeneous Information Networks via Metagraphs. In SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval, page 913–916. ACM, July 2019. Bibtex, PDF
    @inproceedings{fang-2019-m-hin,
    Author = {Fang, Yang and Zhao, Xiang and Huang, Peixin and Xiao, Weidong and de Rijke, Maarten},
    Booktitle = {SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2019-04-14 21:00:49 +0200},
    Date-Modified = {2019-08-02 15:59:43 +0200},
    Month = {July},
    Pages = {913--916},
    Publisher = {ACM},
    Title = {M-HIN: Complex Embeddings for Heterogeneous Information Networks via Metagraphs},
    Year = {2019}}
  • Rolf Jagerman, Harrie Oosterhuis, and Maarten de Rijke. To Model or to Intervene: A Comparison of Counterfactual and Online Learning to Rank from User Interactions. In SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval, page 15–24. ACM, July 2019. Bibtex, PDF
    @inproceedings{jagerman-2019-model,
    Author = {Jagerman, Rolf and Oosterhuis, Harrie and de Rijke, Maarten},
    Booktitle = {SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2019-04-14 16:45:43 +0200},
    Date-Modified = {2019-08-02 15:58:05 +0200},
    Month = {July},
    Pages = {15--24},
    Publisher = {ACM},
    Title = {To Model or to Intervene: A Comparison of Counterfactual and Online Learning to Rank from User Interactions},
    Year = {2019}}
  • Claudio Lucchese, Franco Maria Nardini, Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang, Harrie Oosterhuis, Rolf Jagerman, and Maarten de Rijke. Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning. In SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval, page 1419–1420, ACM, July 2019. Bibtex, PDF
    @inproceedings{lucchese-2019-learning,
    Address = {ACM},
    Author = {Lucchese, Claudio and Nardini, Franco Maria and Pasumarthi, Rama Kumar and Bruch, Sebastian and Bendersky, Michael and Wang, Xuanhui and Oosterhuis, Harrie and Jagerman, Rolf and de Rijke, Maarten},
    Booktitle = {SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2019-05-31 22:47:26 +0200},
    Date-Modified = {2019-08-02 16:00:12 +0200},
    Month = {July},
    Pages = {1419--1420},
    Title = {Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning},
    Year = {2019}}
  • Ana Lucic, Hinda Haned, and Maarten de Rijke. Explaining Predictions from Tree-based Boosting Ensembles. In FACTS-IR: SIGIR 2019 Workshop on Fairness, Accountability, Confidentiality, Transparency and Safety in Information Retrieval, July 2019. Bibtex, PDF
    @inproceedings{lucic-2019-explaining,
    Author = {Lucic, Ana and Haned, Hinda and de Rijke, Maarten},
    Booktitle = {FACTS-IR: SIGIR 2019 Workshop on Fairness, Accountability, Confidentiality, Transparency and Safety in Information Retrieval},
    Date-Added = {2019-05-31 22:21:39 +0200},
    Date-Modified = {2019-05-31 22:38:12 +0200},
    Month = {July},
    Title = {Explaining Predictions from Tree-based Boosting Ensembles},
    Year = {2019}}
  • Muyang Ma, Pengjie Ren, Yujie Lin, Zhumin Chen, Jun Ma, and Maarten de Rijke. $\pi$-Net: A Parallel Information-sharing Network for Cross-domain Shared-account Sequential Recommendations. In SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval, page 685–694. ACM, July 2019. Bibtex, PDF
    @inproceedings{ma-2019-pi-net,
    Author = {Ma, Muyang and Ren, Pengjie and Lin, Yujie and Chen, Zhumin and Ma, Jun and de Rijke, Maarten},
    Booktitle = {SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2019-04-14 16:49:57 +0200},
    Date-Modified = {2019-08-02 15:59:03 +0200},
    Month = {July},
    Pages = {685--694},
    Publisher = {ACM},
    Title = {$\pi$-Net: A Parallel Information-sharing Network for Cross-domain Shared-account Sequential Recommendations},
    Year = {2019}}
  • Alexandra Olteanu, Jean Garcia-Gathright, Maarten de Rijke, and Michael D. Ekstrand. Workshop on Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval (FACTS-IR). In SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval, page 1423–1425. ACM, July 2019. Bibtex, PDF
    @inproceedings{olteanu-2019-workshop,
    Author = {Olteanu, Alexandra and Garcia-Gathright, Jean and de Rijke, Maarten and Ekstrand, Michael D.},
    Booktitle = {SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2019-05-31 22:51:14 +0200},
    Date-Modified = {2019-08-02 16:00:36 +0200},
    Month = {July},
    Pages = {1423--1425},
    Publisher = {ACM},
    Title = {Workshop on Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval (FACTS-IR)},
    Year = {2019}}
  • Jiahuan Pei, Pengjie Ren, and Maarten de Rijke. A Modular Task-oriented Dialogue System Using a Neural Mixture-of-Experts. In WCIS: SIGIR 2019 Workshop on Conversational Interaction Systems. ACM, July 2019. Bibtex, PDF
    @inproceedings{pei-2019-modular,
    Author = {Pei, Jiahuan and Ren, Pengjie and de Rijke, Maarten},
    Booktitle = {WCIS: SIGIR 2019 Workshop on Conversational Interaction Systems},
    Date-Added = {2019-06-01 07:18:46 +0200},
    Date-Modified = {2019-07-14 12:24:23 +0200},
    Month = {July},
    Publisher = {ACM},
    Title = {A Modular Task-oriented Dialogue System Using a Neural Mixture-of-Experts},
    Year = {2019}}
  • Taihua Shao, Fei Cai, Honghui Chen, and Maarten de Rijke. Length-adaptive Neural Network for Answer Selection. In SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval, page 869–872. ACM, July 2019. Bibtex, PDF
    @inproceedings{shao-2019-length-adaptive,
    Author = {Shao, Taihua and Cai, Fei and Chen, Honghui and de Rijke, Maarten},
    Booktitle = {SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2019-04-14 20:59:02 +0200},
    Date-Modified = {2019-08-02 15:59:20 +0200},
    Month = {July},
    Pages = {869--872},
    Publisher = {ACM},
    Title = {Length-adaptive Neural Network for Answer Selection},
    Year = {2019}}
  • Meirui Wang, Pengjie Ren, Lei Mei, Zhumin Chen, Jun Ma, and Maarten de Rijke. A Collaborative Session-based Recommendation Approach with Parallel Memory Modules. In SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval, page 345–354. ACM, July 2019. Bibtex, PDF
    @inproceedings{wang-2019-collaborative,
    Author = {Wang, Meirui and Ren, Pengjie and Mei, Lei and Chen, Zhumin and Ma, Jun and de Rijke, Maarten},
    Booktitle = {SIGIR 2019: 42nd international ACM SIGIR conference on Research and Development in Information Retrieval},
    Date-Added = {2019-04-14 16:52:16 +0200},
    Date-Modified = {2019-08-02 15:58:23 +0200},
    Month = {July},
    Pages = {345--354},
    Publisher = {ACM},
    Title = {A Collaborative Session-based Recommendation Approach with Parallel Memory Modules},
    Year = {2019}}

Paper on incremental sparse Bayesian ordinal regression published in Neural Networks

“Incremental sparse Bayesian ordinal regression” by Chang Li and Maarten de Rijke has been published in the October 2018 issue of Neural Networks. See the journal’s site.

Ordinal Regression (OR) aims to model the ordering information between different data categories, which is a crucial topic in multi-label learning. An important class of approaches to OR models the problem as a linear combination of basis functions that map features to a high-dimensional non-linear space. However, most of the basis function-based algorithms are time consuming. We propose an incremental sparse Bayesian approach to OR tasks and introduce an algorithm to sequentially learn the relevant basis functions in the ordinal scenario. Our method, called Incremental Sparse Bayesian Ordinal Regression (ISBOR), automatically optimizes the hyper-parameters via the type-II maximum likelihood method. By exploiting fast marginal likelihood optimization, ISBOR can avoid big matrix inverses, which is the main bottleneck in applying basis function-based algorithms to OR tasks on large-scale datasets. We show that ISBOR can make accurate predictions with parsimonious basis functions while offering automatic estimates of the prediction uncertainty. Extensive experiments on synthetic and real word datasets demonstrate the efficiency and effectiveness of ISBOR compared to other basis function-based OR approaches.

CIKM 2018 paper on Web-based Startup Success Prediction online

Web-based Startup Success Prediction by Boris Sharchilev, Michael Roizner, Andrey Rumyantsev, Denis Ozornin, Pavel Serdyukov, Maarten de Rijke is online now at this page.

In the paper we consider the problem of predicting the success of startup companies at their early development stages. We formulate the task as predicting whether a company that has already secured initial (seed or angel) funding will attract a further round of investment in a given period of time. Previous work on this task has mostly been restricted to mining structured data sources, such as databases of the startup ecosystem consisting of investors, incubators and startups. Instead, we investigate the potential of using web-based open sources for the startup success prediction task and model the task using a very rich set of signals from such sources. In particular, we enrich structured data about the startup ecosystem with information from a business- and employment-oriented social networking service and from the web in general. Using these signals, we train a robust machine learning pipeline encompassing multiple base models using gradient boosting. We show that utilizing companies’ mentions on the Web yields a substantial performance boost in comparison to only using structured data about the startup ecosystem. We also provide a thorough analysis of the obtained model that allows one to obtain insights into both the types of useful signals discoverable on the Web and market mechanisms underlying the funding process.

The paper will be presented at CIKM 2018 in October 2018.

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