一、简介
Information retrieval (IR) techniques, such as search, recommendation and online advertising, satisfying users’ information needs by suggesting users personalized objects (information or services) at the appropriate time and place, play a crucial role in mitigating the information overload problem. Since the widely use of mobile applications, more and more information retrieval services have provided interactive functionality and products. Thus, learning from interaction becomes a crucial machine learning paradigm for interactive IR, which is based on reinforcement learning. With recent great advances in deep reinforcement learning (DRL), there have been increasing interests in developing DRL based information retrieval techniques, which could continuously update the information retrieval strategies according to users’ real-time feedback, and optimize the expected cumulative long-term satisfaction from users.
Our workshop is a full-day workshop DRL4IR at SIGIR 2021, with the aim to provide a venue, which can bring together academia researchers and industry practitioners (i) to discuss the principles, limitations and applications of DRL for information retrieval, and (ii) to foster research on innovative algorithms, novel techniques, and new applications of DRL to information retrieval.
二、重要时间节点
论文截稿2021年5月30日
录用通知2021年6月19日
研讨会日期2021年7月15日。
三、论文领域
In this workshop, we invite professionals, researchers and technologists of all relevant fields to present the state-of-the-art development and applications, share their envisions about the future of information retrieval with decision making techniques like deep reinforcement learning.
We encourage submissions on a broad range of DRL for knowledge discovery in various domains. Topics of interest include but are not limited to theoretical aspects, algorithms, methods, applications, and systems, such as:
- Deep reinforcement learning (DRL) methods in information retrieval scenarios
- DRL for recommender systems
- DRL for online advertising
- DRL for query expansion and/or reformulation
- DRL for ranking
- DRL for item sampling in traning
DRL in social networks & graph mining
This year we encourage all kinds of papers for submission, including the original and published ones. For the original papers, the authors are free to further submit to any other venues. We invite the submission of full research papers (610 pages) and short papers (24 pages). The accepted papers will be put onto the workshop website. We encourage the authors of accepted papers to put their papers onto arxiv and we will link to the arxiv URLs. Papers must be in English, in PDF format, and in the current ACM two-column conference format. Suitable LaTeX, Word, and Overleaf templates are available from the ACM Website (use the sigconf proceedings template). We will follow a single-blind process and submissions will be evaluated by the program committee based on the quality of the work and its fit to the workshop themes. All the papers are required to be submitted via EasyChair system.
All questions about submissions should be emailed to wnzhang@sjtu.edu.cn or zhaoxi35@msu.edu.
四、组织者
欢迎大家讨论，可以将任何疑问留言在评论栏。
