SIGIR 2020

SIGIR 2020
43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
Event in series	SIGIR
Homepage:	https://sigir.org/sigir2020/
Twitter account:	‎@sigir2020
Submitting link:	https://easychair.org/my/conference?conf=sigir2020
Location
Location:	Xi'an, China
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Important dates
Abstracts:	2020/01/15
Papers:	2020/01/22
Submissions:	2020/01/22
Notification:	2020/04/22
Committees
General chairs:	Yi Chang, Xueqi Cheng, Jimmy Huang
PC chairs:	Jaap Kamps, Vanessa Murdock, Ji-rong Wen
Table of Contents
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Important Dates

Call for Full Papers for SIGIR 2020, Xi’an, China Important dates for full papers:

• Time zone: Anywhere On Earth (AOE)
• Full paper abstracts due: Wed, Jan 15, 2020
• Full papers due: Wed, Jan 22, 2020
• Full paper notifications: Wed, Apr 22, 2020

The annual SIGIR conference is the major international forum for the presentation of new research results, and the demonstration of new systems and techniques, in the broad field of information retrieval (IR). The 43rd ACM SIGIR conference, to be held in Xi'an, China, welcomes contributions related to any aspect of information retrieval and access, including theories and foundations, algorithms and applications, and evaluation and analysis. The conference and program chairs invite those working in areas related to IR to submit high-impact original papers for review.

Committees

General co-Chairs

• Yi Chang, Jilin University, China
• Xueqi Cheng, Chinese Academy of Sciences, China
• Jimmy Huang, York University, Canada

Program co-Chairs

• Jaap Kamps, University of Amsterdam, Netherlands
• Vanessa Murdock, Amazon, United States
• Ji-rong Wen, Renmin University of China, China

Topics

Relevant topics include, but are not limited to:

• Search and Ranking:
• Research on core IR algorithmic topics, including IR at scale, such as:
• Queries and Query Analysis (e.g., query intent, query understanding, query suggestion and prediction, query representation and reformulation, spoken queries).
• Web Search (e.g., ranking at web scale, link analysis, sponsored search, search advertising, adversarial search and spam, vertical search).
• Retrieval Models and Ranking (e.g., ranking algorithms, learning to rank, language models, retrieval models, combining searches, diversity and aggregated search).
• Efficiency and Scalability (e.g., indexing, crawling, compression, search engine architecture, distributed search, metasearch, peer-to-peer search, search in the cloud).

Foundations and Future Directions: Research with theoretical or empirical contributions on new technical or social aspects of IR, especially in more speculative directions or with emerging technologies, such as:

       New Theory (e.g., theoretical models, concepts and foundations of information retrieval and access).
       New Approaches (e.g., as part of a vision for important future IR scenarios).
       New Devices (e.g., consumer devices, wearable computing, neuroinformatics, sensors, Internet-of-Things, vehicles).
       Ethics, Economics, and Politics (e.g., studies on broader implications, norms and ethics, economic value, political impact).
       Perspectives (e.g., like keynotes with visionary reflections on a body of research, the field, theories, models, and methods, providing critical, provocative, creative ideas and insights, with actionable lessons for the near future).

Domain-Specific Applications: Research focusing on domain-specific IR challenges, such as:

• Local and Mobile Search (e.g., location-based search, mobile usage understanding, mobile result presentation, audio and touch interfaces, geographic search, location context in search).
• Social Search (e.g., social networks in search, social media in search, blog and microblog search, forum search).
• Search in Structured Data (e.g., XML search, graph search, ranking in databases, desktop search, email search, entity-oriented search).
• Multimedia Search (e.g., image search, video search, speech and audio search, music search).
• Education (e.g,. search for educational support, peer matching, info seeking in online courses/MOOCs).
• Legal (e.g., e-discovery, patents, other applications in law).
• Health (e.g., medical, genomics, bioinformatics, other applications in health).
• Knowledge Graph Applications (e.g. conversational search, semantic search, entity search, KB question answering, knowledge-guided NLP, search and recommendation).
• Other Applications and Domains (e.g., digital libraries, enterprise, expert search, news search, app search, archival search, new retrieval problems including applications of search technology for social good).

Content Recommendation, Analysis and Classification: Research focusing on recommender systems, rich content representations and content analysis, such as:

• Filtering and Recommending (e.g., content-based filtering, collaborative filtering, recommender systems, recommendation algorithms, zero-query and implicit search, personalized recommendation).
• Document Representation and Content Analysis (e.g., summarization, text representation, linguistic analysis, readability, NLP for search applications, cross- and multi-lingual search, information extraction, opinion mining and sentiment analysis, clustering, classification, topic models).
• Knowledge Aquisition (e.g. information extraction, relation extraction, event extraction, query understanding, human-in-the-loop knowledge aquisition)

Artificial Intelligence, Semantics, and Dialog: Research bridging AI and IR, especially toward deep semantics and dialog with intelligent agents, such as:

• Core AI (e.g. deep learning for IR, embeddings, intelligent personal assistants and agents).
• Question Answering (e.g., factoid and non-factoid question answering, interactive question answering, community-based question answering, question answering systems).
• Conversational Systems (e.g., conversational search interaction, dialog systems, spoken language interfaces, intelligent chat systems).
• Explicit Semantics (e.g. semantic search, named-entities, relation and event extraction).
• Knowledge Representation and Reasoning (e.g., link prediction, knowledge graph completion, query understanding, knowledge-guided query and document representation, ontology modeling).
• Ethics (e.g., algorithmic fairness, accountability, transparency, confidentiality, representativeness, discrimination and harmful bias).

Human factors and interfaces: Research into user-centric aspects of IR including user interfaces, behavior modeling, privacy, interactive systems, such as:

• Mining and Modeling Users (e.g., user and task models, click models, log analysis, behavioral analysis, modeling and simulation of information interaction, attention modeling).
• Interactive Search (e.g., search interfaces, information access, exploratory search, search context, whole-session support, proactive search, personalized search).
• Social Search (e.g., social media search, social tagging, crowdsourcing).
• Collaborative Search (e.g., human-in-the-loop, knowledge aquisition).
• Information Security (e.g., privacy, surveillance, censorship, encryption, security).

Evaluation: Research that focuses on the measurement and evaluation of IR systems, such as:

• User-centered Evaluation (e.g., user experience and performance, user engagement and search task design).
• System-centered Evaluation (e.g., novel types of test collections, evaluation metrics).
• Beyond Cranfield (e.g., online evaluation, task-based, session-based, multi-turn, interactive search).
• Beyond Labels (e.g., simulation, implicit signals, eye-tracking and physiological approaches, such as fMRI).
• Beyond Effectiveness (e.g., usefulness, urgency, value, utility, credibility, authority, diversity).
• Methodology (e.g., statistical methods and reproducibility issues in IR evaluation).