中国计算机学会(CCF)推荐学术会议-A(数据库/数据挖掘/内容检索):SIGIR 2026

SIGIR 2026

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 49th ACM SIGIR conference will be run as an in-person conference from July 20 to 24, 2026 in Melbourne | Naarm, Australia.

重要信息

CCF推荐:A(数据库/数据挖掘/内容检索)

录用率:22.3%(239/1071,2025年Full Papers)

时间地点:2026年7月20日-墨尔本·澳大利亚

截稿时间:2026年1月15日

大会官网:https://sigir2026.org/en-AU

Call for Papers

Search and Ranking. Research on core IR algorithmic topics.

System, Efficiency and Scalability. Research on search system aspects that relate to the efficiency of the system and/or its scalability.

Recommender Systems. Research focusing on recommender systems, rich content representations and content analysis for recommendation.

Machine Learning for IR. Research bridging ML and IR.

Natural Language Processing for IR. Research bridging NLP and IR.

Conversational or Agentic IR. Research focusing on developing intelligent IR systems that can understand and respond to users' natural language queries and provide relevant information or recommendations through interactive conversations.

Humans and Interfaces. Research into user-centric aspects of IR including user interfaces, behavior modeling, privacy, interactive systems.

Datasets, Benchmarks, and Evaluations for IR. Research that focuses on the measurement and evaluation of IR systems.

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

Multi Modal IR. Theoretical, algorithmic or novel practical solutions addressing problems across the domain of multimedia and IR.

Domain-Specific IR Applications. Research focusing on domain-specific IR challenges.

Other IR Topics. Any IR Research that does not fall into any of the areas above.

Submission Guidelines

Submissions of full research papers must be in English, in PDF format, and be at most 9 pages (including figures, tables, proofs, appendixes, acknowledgments, and any content except references) in length, with unrestricted space for references, in the current ACM two-column conference format.

Suitable LaTeX, Word, and Overleaf templates are available from the ACM Website (use "sigconf" proceedings template for LaTeX and the Interim Template for Word). ACM's CCS concepts and keywords are required for review.

For LaTeX, the following should be used:

\documentclasssigconf,natbib=true,anonymous=true{acmart}

Submissions must be anonymous and should be submitted electronically.

相关推荐
小奶包他干奶奶6 小时前
AI学习——1、机器学习概念
人工智能·机器学习
Angeldream12310 小时前
第 10 章 医学影像伦理与安全
图像处理·人工智能·python·安全·机器学习·医学影像
吕布辕门11 小时前
DeepSeek 大模型落地应用与价值实现指南
人工智能·机器学习
龙腾AI白云12 小时前
大模型检索增强生成(RAG)的技术原理与架构设计
数据库·python·机器学习·知识图谱
夏天的清晨14 小时前
聚类与2-OPT
人工智能·机器学习·聚类
FanfanZainuli14 小时前
减肥APP智能化技术演进:从“内容推荐“到“AI驱动的个性化闭环“
人工智能·深度学习·机器学习
Light6015 小时前
每晚 1000 万条警报:望远镜的瓶颈已经变成算法
机器学习·ai for science·超新星·引力透镜·vera rubin 天文台·事件警报
高洁0116 小时前
大模型检索增强生成(RAG)的技术原理与架构设计
人工智能·深度学习·机器学习·django·迁移学习
数聚天成DeepSData16 小时前
两份名录里的同名机构,主键该怎么合并
人工智能·深度学习·机器学习·数据集·deepsdata
硅谷秋水17 小时前
自演化智能体驾驭
人工智能·机器学习·语言模型