The SIGIR 2022 workshop program will host 8 compelling workshops that highlight the breadth of interesting problems being explored in the field of information retrieval and that explore novel ideas and emerging areas in the field.
All workshops will be held on Friday July 15th at the conference venue, Círculo de Bellas Artes.
Full Day Workshops
- 6th Workshop on eCommerce (ECOM)
- 3rd Workshop on Deep Reinforcement Learning for Information Retrieval (DRL4IR)
- 7th Workshop on Search-Oriented Conversational Artificial Intelligence (SCAI)
- 3rd Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech)
- 1st Workshop on Reaching Efficiency in Neural Information Retrieval (ReNeuIR)
- 10th Workshop on News Recommendation and Analytics (INRA)
Half Day Workshops
- 1st Workshop on Measuring the Quality of Explanations in Recommender Systems (QUARE)
- 3rd International Workshop on Investigating Learning During Web Search (IWILDS)
Organizers: Ajinkya Kale (Adobe), Surya Kallumadi (Lowe’s), Tracy Holloway King (Adobe), Shervin Malmasi (Amazon), Maarten de Rijke (University of Amsterdam), Jacopo Tagliabue (Coveo)
The SIGIR Workshop on eCommerce will serve as a platform for publication and discussion of Information Retrieval and NLP research & their applications in the domain of eCommerce. This workshop will bring together practitioners and researchers from academia and industry to discuss the challenges and approaches to product search and recommendation in eCommerce.
The theme of this year’s workshop is Bridging IR Metrics and Business Metrics and Multi-objective Optimization.
SIGIR eCom is a full day workshop taking place on Thursday, July 15, 2022 in conjunction with SIGIR 2022. SIGIR eCom’22 will be a hybrid workshop.
Organizers: Xiangyu Zhao (City University of Hong Kong), Xin Xin (Shandong University), Weinan Zhang (Shanghai Jiao Tong University), Li Zhao (Microsoft Research Asia), Dawei Yin (Baidu), Grace Hui Yang (Georgetown University)
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.
Organizers: Svitlana Vakulenko (Amazon Alexa AI), Ondrej Dusek (Charles University), Leigh Clark (Swansea University), Gustavo Penha (Delft University of Technology), Vaishali Pal (University of Amsterdam), Vaibhav Adlakha (McGill University)
This workshop is intended as a discussion platform on Conversational AI for intelligent information access, bringing together researchers and practitioners across natural language processing, information retrieval, machine learning and human-computer interaction fields. Among other topics, we will discuss design, evaluation and human factors in relation to automating information-seeking dialogues. The workshop will also feature a shared task on Conversational Question Answering.
Organizers: Ralf Krestel (HPI Potsdam), Hidir Aras (FIZ Karlsruhe), Allan Hanbury (TU Wien), Linda Andersson (Artificial Researcher), Florina Piroi (Data Science Studio), Dean Alderucci (CMU)
PatentSemTech aims to establish a long-term collaboration and a two-way communication channel between the IP industry and academia from relevant fields such as natural-language processing (NLP), text and data mining (TDM) and semantic technologies (ST) in order to explore and transfer new knowledge, methods and technologies for the benefit of industrial applications as well as support research in applied sciences for the IP and neighbouring domains.
Organizers: Sebastian Bruch (Pinecone), Claudio Lucchese (Università Ca’ Foscari di Venezia), Franco Maria Nardini (ISTI-CNR)
The ReNeuIR Workshop aims to foster discussion and collaboration on holistic evaluation of methods in the age of neural information retrieval (NIR), noting that efficacy matters but so does the computational cost incurred to achieve it. In particular, the workshop promotes the following notions and encourages the community to raise and debate questions on the following themes: justification of the ever-growing model complexity through appropriate empirical analysis, training and inference efficiency and evaluation and reporting.
Organizers: Özlem Özgöbek (Associate Professor, NTNU) Andreas Lommatzsch (PostDoc, DAI Lab, TU Berlin), Benjamin Kille (PostDoc, NorwAI, NTNU), Peng Liu (PostDoc, NorwAI, NTNU), Edward C. Malthouse (Professor, Northwestern University) and Jon Atle Gulla (Professor, NorwAI, NTNU)
Daily news consumption has crucial importance where it affects personal beliefs, decision making, political voting and world views in general. The news ecosystem has experienced drastic changes over the last decade. News consumption has shifted online and increasingly towards social media. On digital platforms such as news portals and social media, where personalization has more importance, the news is filtered and ranked even without users’ awareness. Therefore, we encounter challenges such as lack of transparency, diversity, and other ethical considerations while trying to generate the most suitable personalized recommendations for the users. The 10th International Workshop on News Recommendation and Analytics (INRA 2022 in conjunction with ACM SIGIR 2022) invites scholars from diverse disciplines to discuss topics related to news recommendation, including but not limited to technical, societal, and ethical aspects.
Organizers: Alessandro Piscopo (BBC), Oana Inel (University of Zurich), Sanne Vrijenhoek (University of Amsterdam), Martijn Millecamp (AE) and Krisztian Balog (Google)
Measuring the Quality of Explanations in Recommender Systems—is the first workshop that aims to promote discussion upon future research and practice directions around evaluation methodologies for explanations in recommender systems. This half day workshop aims to promote discussion and outline previous, current, and future research directions in the field of explanations in recommender systems, by bringing together researchers and practitioners from academia and industry. In particular, we want to stimulate reflections around methods to systematically and holistically assess explanation approaches and goals, at the interplay between organisational and human values.
Organizers: Anett Hoppe (Leibniz Information Centre for Science & Technology), Jiqun Liu (University of Oklahoma), Ran Yu (University of Bonn)
Web search is one of the most ubiquitous online activities and often used as a starting point to learn, i. e., to acquire or extend one’s knowledge about certain topics or procedures. When learning by searching the Web, individuals are confronted with an unprecedented amount of information in various forms and varying quality. Thus, successful learning on the Web requires high degrees of self-regulation and should be supported by the adequate design of search, recommendation, and training tools. This creates a highly interdisciplinary research area at the intersection of information retrieval, human-computer interaction, psychology, and educational sciences. Search as Learning (SAL) research examines the relationships between querying, navigation, media consumption behavior, and the learning outcomes during Web search, how they can be measured, predicted, and supported.