会议信息

AIST' 2026: International Conference on Analysis of Images, Social Networks and Texts

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截稿日期:
2026-07-08 Extended
通知日期:
2026-08-10
会议日期:
2026-10-16
会议地点:
Astana, Kazakhstan
届数:
13
浏览: 1026   关注: 0   参加: 0

会伴指数 (CP-I)

47.8 / 100
全站第 2,126 名 / 共 5,693 个会议 · 前 38%

信息系统与 Web 第 99 / 253

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
71
社区关注 (10%)
8
资料公开度 (15%)
35

用到的输入: 有据可查的届次：13 · 过去 24 个月打开过本页的研究者：2 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-03

征稿

AIST' 2026 (International Conference on Analysis of Images, Social Networks and Texts) is an academic conference held in Astana, Kazakhstan on 2026-10-16. The paper submission deadline is 2026-07-08 (extended). Acceptance notifications are sent on 2026-08-10.

Dear colleagues, We are excited to invite you to submit a paper to AIST-2026, a scientific conference on Analysis of Images, Social Networks, and Texts. The conference is intended for researchers and practitioners interested in data science focusing on innovative applications of data analysis and machine learning techniques to image processing, analysis of network data, text processing, and other domains, such as economics or geographic information systems. The conference is intended for computer scientists and practitioners whose research interests are related to data science. The twelve previous editions of the AIST conference held in 2012-2024 attracted a significant number of students, researchers, academics, and engineers working on the analysis of images, texts, and social networks. The broad scope of AIST makes it an event where researchers from different domains, exploiting various data analysis techniques, can meet and exchange ideas. The conference allows specialists from different fields to meet each other, present their work, and discuss both theoretical and practical aspects of their data analysis problems. Another important aim of the conference is to stimulate scientists and people from the industry to benefit from the knowledge exchange and identify possible grounds for fruitful collaboration. Similar to the previous years, the main volume of the conference proceedings will be published in the Springer’s in Lecture Notes in Computer Science (LNCS) series. Submisson Topics We are encouraging submission on any application of deep learning and data analysis including, but not limited to the following topics: Analysis of images and video Analytics for geoinformation systems Computational linguistics Core data mining and machine learning techniques Discovering and analyzing processes using event data Deep learning applications Educational data mining Game analytics Machine learning and data mining for economics and social sciences Natural language processing and applications Optimization problems in complex networks Recommendational systems and collaborative technologies Semantic web and ontologies Social network analysis
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