明年3月前CCF人工智能会议截稿汇总--ICCV, IJCAI, SIGIR等13条_ijcai2024截稿日期

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ESWC2023

会议全称：Extended Semantic Web Conference

录用率：21年 25.15%（42/167)

CCF分级：数据库／数据挖掘／内容检索C

截稿时间：22.12.8（注册）

录用通知时间：23.2.23

官网链接：https://2023.eswc-conferences.org/

征稿范围：

Semantic Web research and applications, such as Linked Data and Knowledge Graphs, Ontologies, Reasoning, Natural Language Processing and Understanding, Machine and Deep Learning, Information Retrieval, Data Quality and Data Integration, and Semantic Data Management, as well as related applications from Life Sciences, eGovernment, Business, Manufacturing, eScience, Emergency and Crisis Management, Cultural Heritage, Tourism, Autonomous Systems, etc. Posters and demos will be presented in a separate, interactive session, providing the opportunity for engaging in discussions and direct exchange

ICME2023

会议全称：International Conference on Multimedia & Expo

录用率：22年 29.65%（381/1285）

CCF分级：计算机图形学与多媒体B

截稿时间：23.12.15

录用通知时间：23.3.12

官网链接：https://www.2023.ieeeicme.org/

征稿范围：

SIGIR2023

会议全称：International ACM SIGIR Conference on Research and Development in Information Retrieval

录用率：22年 20.28%（161/794）

CCF分级：数据库／数据挖掘／内容检索A

截稿时间：23.1.24(注册）23.1.31（投稿）

录用通知时间：23.4.4

官网链接：https://sigir.org/sigir2023/

征稿范围：

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, aggregated search, dealing with bias).

  • Efficiency and scalability (e.g., indexing, crawling, compression, search engine architecture, distributed search, metasearch, peer-to-peer search, search in the cloud).

  • Theoretical models and foundations of information retrieval and access (e.g., new theory, fundamental concepts, theoretical analysis).

Search Recommendation & Content Analysis for Search and Recommendation. Research focusing on recommender systems, rich content representations and content analysis, such as:

• • Filtering and recommendation (e.g., content-based filtering, collaborative filtering, recommender systems, recommendation algorithms, zero-query and implicit search, personalized recommendation).

  • Document representation and content analysis for search or recommendation (e.g., cross-lingual and multilingual search, NLP: summarization, text representation, linguistic analysis, readability, opinion mining and sentiment analysis, clustering, classification, topic models for search and recommendation).

  • Knowledge acquisition (e.g. information extraction, relation extraction, event extraction, query understanding, human-in-the-loop knowledge acquisition).

Machine Learning and Natural Language Processing for Search and Recommendation. Research bridging ML, NLP, and IR.

• • Core ML (e.g. deep learning for IR, embeddings, intelligent personal assistants and agents, unbiased learning).

  • 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).

Humans 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 acquisition).

  • Information security (e.g., privacy, surveillance, censorship, encryption, security).

  • User studies comparing theory to human behaviour for search and recommendation.

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, search task design).

  • System-centered evaluation (e.g., evaluation metrics, test collections, experimental design, evaluation pipelines, crowdsourcing).

  • 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 signals).

  • Beyond effectiveness (e.g., value, utility, usefulness, diversity, novelty, urgency, freshness, credibility, authority).

  • Methodology (e.g., statistical methods, reproducibility, dealing with bias, new experimental approaches, metrics for metrics).

Fairness, Accountability, Transparency, Ethics, and Explainability (FATE) in IR. Research on aspects of fairness and bias in search and recommender systems.

• • Fairness, accountability, transparency (e.g. confidentiality, representativeness, discrimination and harmful bias).

  • Ethics, economics, and politics (e.g., studies on broader implications, norms and ethics, economic value, political impact, social good).

  • Two-sided search and recommendation scenarios (e.g. matching users and providers, marketplaces).

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).

  • 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).

IJCNN2023

会议全称：Joint Conference on Neural Networks

录用率：21年 58.2%(1183/2032)

CCF分级：人工智能C

截稿时间：23.1.31

录用通知时间：23.3.31

官网链接：https://2023.ijcnn.org/

征稿范围：

COLT2023

会议全称：Conference on Learning Theory

录用率：20年 30.93%（120/388）

CCF分级：人工智能B

截稿时间：23.2.10

录用通知时间：23.5.15

官网链接：http://www.learningtheory.org/colt2023/

征稿范围：

• Design and analysis of learning algorithms

• Statistical and computational complexity of learning

• Optimization methods for learning, including online and stochastic optimization

• Theory of artificial neural networks, including deep learning

• Theoretical explanation of empirical phenomena in learning

• Supervised learning

• Unsupervised, semi-supervised learning, domain adaptation

• Learning geometric and topological structures in data, manifold learning

• Active and interactive learning

• Reinforcement learning

• Online learning and decision-making

• Interactions of learning theory with other mathematical fields

• High-dimensional and non-parametric statistics

• Kernel methods

• Causality

• Theoretical analysis of probabilistic graphical models

• Bayesian methods in learning

• Game theory and learning

• Learning with system constraints (e.g., privacy, fairness, memory, communication)

• Learning from complex data (e.g., networks, time series)

• Learning in neuroscience, social science, economics and other subjects

IROS2023

会议全称：Intelligent Robots and Systems

录用率：18年 46.44%（1254/2700）

CCF分级：人工智能C

截稿时间：23.3.1

录用通知时间：23.6.30

官网链接：https://ieee-iros.org/

征稿范围：

intelligent robots and smart machines, emphasizing future directions and the latest approaches, designs, and outcomes

ICCV2023

会议全称：International Conference on Computer Vision

录用率：21年 26.2%（1612/6152）

CCF分级：人工智能A

截稿时间：23.3.8

录用通知时间：23.7.13

官网链接：https://iccv2023.thecvf.com/

征稿范围：

KR2023

会议全称：Knowledge Representation and Reasoning

录用率：20年 34.44%（83/241）

CCF分级：人工智能B

截稿时间：23.3.3(注册）23.3.14（投稿）

录用通知时间：23.5.18

官网链接：https://kr.org/KR2023/

征稿范围：

• Applications of KR
• Argumentation
• Belief revision and update, belief merging
• Commonsense reasoning
• Computational aspects of knowledge representation
• Concept formation, similarity-based reasoning
• Contextual reasoning
• Decision making
• Description logics
• Explanation finding, diagnosis, causal reasoning, abduction
• Geometric, spatial, and temporal reasoning
• Inconsistency- and exception-tolerant reasoning
• Knowledge acquisition
• Knowledge graphs and open linked data
• Knowledge representation languages
• KR and automated reasoning (satisfiability, QBF, model counting, knowledge compilation)
• KR and autonomous agents and multi-agent systems
• KR and cognitive modelling
• KR and cognitive reasoning
• KR and cognitive robotics
• KR and cognitive systems
• KR and cyber security
• KR and education
• KR and game theory
• KR and machine learning, inductive logic programming,
• KR and natural language processing and understanding
• KR and the Web, Semantic Web
• Logic programming, answer set programming
• Modeling and reasoning about preferences
• Multi- and order-sorted representations and reasoning
• Non-monotonic logics, default logics, conditional logics
• Ontology-based data access, integration, and exchange
• Ontology formalisms and models
• Philosophical foundations of KR
• Qualitative reasoning, reasoning about physical systems
• Reasoning about actions and change, action languages
• Reasoning about constraints, constraint programming
• Reasoning about knowledge, beliefs, and other mental attitudes

• Uncertainty, vagueness, many-valued and fuzzy logics

ICDAR2023

会议全称：International Conference on Document Analysis and Recognition

录用率：21年 53.53%(182/340)

CCF分级：人工智能C

截稿时间：23.1.15

录用通知时间：23.3.26

官网链接：https://icdar2023.org/

征稿范围：

Document image processing
Physical and logical layout analysis
Text and symbol recognition
Handwriting recognition
Document analysis systems
Document classification
Indexing and retrieval of documents
Document synthesis
Extracting document semantics
NLP for document understanding
Office automation
Graphics recognition
Human document interaction
Document Representation Modeling

Structured document generation
Multimedia document analysis
Mobile text recognition
Pen-based document analysis
Scene text detection and recognition
Recognition of tables and formulas
Historical document analysis
Signature verification
Document summarization and translation
Document forensics and provenance
Medical document analysis
Document analysis for social good
Document analysis for literature search
Gold-standard benchmarks and datasets

VLDB2023

会议全称：Very Large Data Bases

录用率：20年 21.40%（104/486）

CCF分级：数据库／数据挖掘／内容检A

截稿时间：1st of every month 5 p.m. PST,until March 2023

录用通知时间：15th of the next month following the deadline

官网链接：https://www.vldb.org/2023/

征稿范围：

data management, database and information systems research

IJCAI2023

会议全称：International Joint Conference on Artificial Intelligence

录用率：22年 15.02%（681/4535）

CCF分级：人工智能A

截稿时间：

录用通知时间：

官网链接：https://ijcai-23.org/

征稿范围：

Submissions to IJCAI 2023 should report significant, original, and previously unpublished results on any aspect of artificial intelligence. Papers on novel AI research problems, AI techniques for novel application domains, and papers that cross discipline boundaries within AI are especially encouraged.

ACL2023

会议全称：Annual Meeting of the Association for Computational Linguistics

录用率：21年24.5% (571/2327)

CCF分级：人工智能A

截稿时间：直接投递（非ARR）通道摘要注册截止时间23.01.13，论文提交截止时间23.1.20

录用通知时间：23.5.1

官网链接：https://2023.aclweb.org/

征稿范围：

Computational Social Science and Cultural Analytics

Dialogue and Interactive Systems

Discourse and Pragmatics

Ethics and NLP

Generation

Information Extraction

Information Retrieval and Text Mining

Interpretability and Analysis of Models for NLP

Language Grounding to Vision, Robotics and Beyond

Multilingualism and Language Contact: Code-switching, Representation Learning, Cross-lingual transfer

Linguistic Theories, Cognitive Modeling, and Psycholinguistics

Machine Learning for NLP

Machine Translation

NLP Applications

Phonology, Morphology, and Word Segmentation

Question Answering

Resources and Evaluation

Semantics: Lexical

Semantics: Sentence-level Semantics, Textual Inference, and Other Areas

Sentiment Analysis, Stylistic Analysis, and Argument Mining

Speech and Multimodality

Summarization

Syntax: Tagging, Chunking and Parsing

Theme Track (see below)

ICMR2023

会议全称：ACM International Conference on Multimedia Retrieval

录用率：22年 34.39% （54/157）

CCF分级：计算机图形学B

截稿时间：2023.1.31

录用通知时间：2023.3.31

官网链接：https://icmr2023.org/

征稿范围：

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