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Academics 🎓 (In CS)

[TOC]

Res

Related Topics

(CS) Academics Roadmap & Tool Chain

International Opportunities

FAQ - Academia and Research /📌 PhD Candidate /Academic Researcher ?

Education

Publications

期刊等级的划分: 北大核心 南大核心 SCI, Science Citation Index SSCI,Social Sciences Citation Index CSSCI,中文社会科学引文索引

SCI期刊搜索 - 最新影响因子查询

中国科学院文献情报中心期刊分区表 中科院分期表不是免费使用的,如需查询需要单位购买😅

https://www.nature.com/nature-index/institution-outputs/generate/all/global/all Nature Index

Others

https://hoochanlon.github.io/hamulete/ https://github.com/hoochanlon/hamulete/tree/master 🏔️国立台湾大学、新加坡国立大学、早稻田大学、东京大学,中央研究院(台湾)以及中国重点高校及科研机构,社科、经济、数学、博弈论、哲学、系统工程类学术论文等知识库。 (This repo has been cloned to local!🥰 -- notes from miro)

https://github.com/context-labs/aella-data-explorer Interactive visualization and exploration of scientific papers from the Aella open science dataset. This project is a collaboration between Inference.net and LAION. LAION curated the original dataset which is about ~100m scrapped scientific and research articles and Inference.net fine-tuned a custom model to extract structured summaries from the articles. This repo contains a visual explorer for a small subset of the extracted dataset. View the live explorer at https://aella.inference.net.

😈 Beyond Academics...

👍 https://github.com/ShiArthur03/ShiArthur03 https://github.com/ShiArthurX/ShiArthurX https://archive.softwareheritage.org/browse/origin/directory/?origin_url=https://github.com/ShiArthur03-thu/ShiArthur03-thu

2024.7.12 原仓库不知道能存在多久。我在本地每天会进行备份仓库的更新。

2024.9.17 原仓库和作者都被删除了。本地的备份还在。

大家好,我是来自M78星云的SBC。我将为你们讲述在我的世界中有关于我的故事,希望你们能够持续关注并真正学习到我想要教给你们的学术技巧,让新的学术思维传承下去。如果这与你们的世界有任何雷同之处,纯属巧合。我相信在任何一个世界当中,每个人都有属于自己的底色:清者自清,浊者自浊。

我,SBC,博士,华清大学“水木学者”,国家级人才计划青年拔尖人才(29岁获得,中国历史上最年轻),于华清大学电机工程与应用电子技术系获得学士和博士学位。主要研究方向为电力电子混杂系统动力学表征、多尺度建模仿真及其工业软件。详细介绍可以在此处找到。视频介绍可以在这里找到,本教程的电子版pdf可通过https://github.com/ShiArthur03 找到。

🎬 https://space.bilibili.com/1010101551?spm_id_from=333.337.0.0 来自星星的何教授 成都省蒲江县人,某地外星球球立大学副教授,法号依托大师。著名理论物理学渣,资深科研狗,著名小镇做题家。

🏁 Don't Miss the Deadline!!!

General

Intro

Universe, Self-Awareness, and Intelligence

FAQ - Academia and Research给各位天命人的劝退信

Research Methodology

(CS) Academics Roadmap & Tool Chain

Academic Publications & Venues

Academic Venues in Computer Science

📈 Bibliometrics

how_research_is_done.excalidraw|1000

Bib-Management

🔗 https://sustech.libguides.com/c.php?g=934045

文献计量学提供一种评价科研文献学术影响力的定量分析方法,可以与定性评价方法如同行评审一起使用,以提供学术影响力证明。计量指标可在论文、期刊、学者层面评价科研文献的影响力,帮助研究人员在申请工作、晋升或研究经费时提供其科研表现的证明。常用的计量指标包括被引频次、学科规范化的引文影响力、期刊影响因子、h指数等。

文献计量学与科研影响力

期刊评价与投稿

科研评价与分析平台

论文收录引用检索证明

* Bibliometrics Related Indexes 🙈

World University Ranking

Journal/Conference Evaluation

Research Entity /Fields Research

Specific Academical Areas in CS & IT

[!links] ↗ 🌲 Road To CS /2️⃣ CS Specific Fields / CS Applications🌲 Road To CS /CS & IT in Different AspectsIntro to Computer Science /The Domain Knowledge of CS

https://en.wikipedia.org/wiki/ACM_Computing_Classification_System https://www.acm.org/publications/class-2012 https://dl.acm.org/ccs ACM CCS 2012

  1. Hardware
    • Printed circuit boards
    • Communication hardware, interfaces and storage
    • Integrated circuits
    • Very large scale integration design
    • Power and energy
    • Electronic design automation
    • Hardware validation
    • Hardware test
    • Robustness
    • Emerging technologies
  2. Software and its Engineering
    • Software organization and properties
      • Contextual software domains
        • E-commerce infrastructure
        • Software infrastructure
        • Operating systems
        • Virtual worlds software
      • Software system structures
        • Embedded software
        • Software architectures
        • Software system models
        • Ultra-large-scale systems
        • Distributed systems organizing principles
        • Real-time systems software
        • Abstraction, modeling and modularity
      • Software functional properties
        • Correctness
        • Formal methods
      • Extra-functional properties
        • Interoperability
        • Software performance
        • Software reliability
        • Software fault tolerance
        • Software safety
        • Software usability
    • Software notations and tools
      • General programming languages
        • Language types
        • Language features
      • Formal language definitions
        • Syntax
        • Semantics
      • Compilers
        • Interpreters
        • Incremental compilers
        • Retargetable compilers
        • Just-in-time compilers
        • Dynamic compilers
        • Translator writing systems and compiler generators
        • Source code generation
        • Runtime environments
        • Preprocessors
        • Parsers
      • Context specific languages
        • Markup languages
        • Scripting languages
        • Domain specific languages
        • Specialized application languages
        • API languages
        • Graphical user interface languages
        • Window managers
        • Command and control languages
        • Macro languages
        • Programming by example
        • State based definitions
        • Visual languages
        • Interface definition languages
      • System description languages
        • Design languages
        • Unified Modeling Language (UML)
        • Architecture description languages
        • System modeling languages
        • Orchestration languages
        • Integration frameworks
        • Specification languages
      • Development frameworks and environments
        • Object oriented frameworks
        • Software as a service orchestration system
        • Integrated and visual development environments
        • Application specific development environments
      • Software configuration management and version control systems
      • Software libraries and repositories
      • Software maintenance tools
    • Software creation and management
      • Designing software
        • Requirements analysis
        • Software design engineering
        • Software design tradeoffs
        • Software implementation planning
      • Software development process management
        • Software development methods
        • Risk management
      • Software development techniques
        • Software prototyping
        • Object oriented development
        • Flowcharts
        • Reusability
        • Error handling and recovery
        • Automatic programming
      • Software verification and validation
        • Software prototyping
        • Operational analysis
        • Software defect analysis
        • Fault tree analysis
        • Process validation
        • Formal software verification
        • Empirical software validation
      • Software post-development issues
        • Software reverse engineering
        • Documentation
        • Backup procedures
        • Software evolution
        • Software version control
        • Maintaining software
        • System administration
      • Collaboration in software development
        • Open source model
        • Programming teams
      • Search-based software engineering
  3. Computer Systems Organization
    • Architectures
    • Embedded and cyber-physical systems
    • Real-time systems
    • Dependable and fault-tolerant systems and networks
  4. Networks
    • Network architectures
    • Network protocols
    • Network components
    • Network algorithms
    • Network performance evaluation
    • Network properties
    • Network services
    • Network types
  5. Theory of Computation
    • Models of computation
    • Formal languages and automata theory
    • Computational complexity and cryptography
    • Logic
    • Design and analysis of algorithms
    • Randomness, geometry and discrete structures
    • Theory and algorithms for application domains
    • Semantics and reasoning
  6. Mathematics of Computing
    • Discrete mathematics
    • Probability and statistics
    • Mathematical software
    • Information theory
    • Mathematical analysis
    • Continuous mathematics
  7. Computing Methodologies
    • Symbolic and algebraic manipulation
    • Parallel computing methodologies
    • Artificial intelligence
      • Natural language processing
        • Information extraction
        • Machine translation
        • Discourse, dialogue and pragmatics
        • Natural language generation
        • Speech recognition
        • Lexical semantics
        • Phonology / morphology
        • Language resources
      • Knowledge representation and reasoning
        • Description logics
        • Semantic networks
        • Nonmonotonic, default reasoning and belief revision
        • Probabilistic reasoning
        • Vagueness and fuzzy logic
        • Causal reasoning and diagnostics
        • Temporal reasoning
        • Cognitive robotics
        • Ontology engineering
        • Logic programming and answer set programming
        • Spatial and physical reasoning
        • Reasoning about belief and knowledge
      • Planning and scheduling
        • Planning for deterministic actions
        • Planning under uncertainty
        • Multi-agent planning
        • Planning with abstraction and generalization
        • Robotic planning
          • Evolutionary robotics
      • Search methodologies
        • Heuristic function construction
        • Discrete space search
        • Continuous space search
        • Randomized search
        • Game tree search
        • Abstraction and micro-operators
        • Search with partial observations
      • Control methods
        • Robotic planning
          • Evolutionary robotics
        • Computational control theory
        • Motion path planning
      • Philosophical/theoretical foundations of artificial intelligence
        • Cognitive science
        • Theory of mind
      • Distributed artificial intelligence
        • Multi-agent systems
        • Intelligent agents
        • Mobile agents
        • Cooperation and coordination
      • Computer vision
        • Computer vision tasks
          • Biometrics
          • Scene understanding
          • Activity recognition and understanding
          • Video summarization
          • Visual content-based indexing and retrieval
          • Visual inspection
          • Vision for robotics
          • Scene anomaly detection
        • Image and video acquisition
          • Camera calibration
          • Epipolar geometry
          • Computational photography
          • Hyperspectral imaging
          • Motion capture
          • 3D imaging
          • Active vision
        • Computer vision representations
          • Image representations
          • Shape representations
          • Appearance and texture representations
          • Hierarchical representations
        • Computer vision problems
          • Interest point and salient region detections
          • Image segmentation
          • Video segmentation
          • Shape inference
          • Object detection
          • Object recognition
          • Object identification
          • Tracking
          • Reconstruction
          • Matching
    • Machine learning
      • Learning paradigms
        • Supervised learning
          • Ranking
          • Learning to rank
          • Supervised learning by classification
          • Supervised learning by regression
          • Structured outputs
          • Cost-sensitive learning
        • Unsupervised learning
          • Cluster analysis
          • Anomaly detection
          • Mixture modeling
          • Topic modeling
          • Source separation
          • Motif discovery
          • Dimensionality reduction and manifold learning
        • Reinforcement learning
          • Sequential decision making
          • Inverse reinforcement learning
          • Apprenticeship learning
          • Multi-agent reinforcement learning
          • Adversarial learning
        • Multi-task learning
          • Transfer learning
          • Lifelong machine learning
          • Learning under covariate shift
      • Learning settings
        • Batch learning
        • Online learning settings
        • Learning from demonstrations
        • Learning from critiques
        • Learning from implicit feedback
        • Active learning settings
        • Semi-supervised learning settings
      • Machine learning approaches
        • Classification and regression trees
        • Kernel methods
          • Support vector machines
          • Gaussian processes
        • Neural networks
        • Logical and relational learning
          • Inductive logic learning
          • Statistical relational learning
        • Learning in probabilistic graphical models
          • Maximum likelihood modeling
          • Maximum entropy modeling
          • Maximum a posteriori modeling
          • Mixture models
          • Latent variable models
          • Bayesian network models
        • Learning linear models
          • Perceptron algorithm
        • Factorization methods
          • Non-negative matrix factorization
          • Factor analysis
          • Principal component analysis
          • Canonical correlation analysis
          • Latent Dirichlet allocation
        • Rule learning
        • Instance-based learning
        • Markov decision processes
        • Partially-observable Markov decision processes
        • Stochastic games
        • Learning latent representations
          • Deep belief networks
        • Bio-inspired approaches
          • Artificial life
          • Evolvable hardware
          • Genetic algorithms
          • Genetic programming
          • Evolutionary robotics
          • Generative and developmental approaches
      • Machine learning algorithms
        • Dynamic programming for Markov decision processes
          • Value iteration
          • Q-learning
          • Policy iteration
          • Temporal difference learning
          • Approximate dynamic programming methods
        • Ensemble methods
          • Boosting
          • Bagging
        • Spectral methods
        • Feature selection
        • Regularization
      • Cross-validation
    • Modeling and simulation
    • Computer graphics
    • Distributed computing methodologies
    • Concurrent computing methodologies
  8. Information Systems
    • Data management systems
    • Information storage systems
    • Information systems applications
    • World Wide Web
    • Information retrieval
  9. Security and privacy
    • Cryptography
      • Key management
      • Public key (asymmetric) techniques
        • Digital signatures
        • Public key encryption
      • Symmetric cryptography and hash functions
        • Block and stream ciphers
        • Hash functions and message authentication codes
      • Cryptanalysis and other attacks
      • Information-theoretic techniques
      • Mathematical foundations of cryptography
    • Formal methods and theory of security
      • Trust frameworks
      • Security requirements
      • Formal security models
      • Logic and verification
    • Security services
      • Authentication
        • Biometrics
        • Graphical / visual passwords
        • Multi-factor authentication
      • Access control
      • Pseudonymity, anonymity and untraceability
      • Privacy-preserving protocols
      • Digital rights management
      • Authorization
    • Intrusion/anomaly detection and malware mitigation
      • Malware and its mitigation
      • Intrusion detection systems
        • Artificial immune systems
      • Social engineering attacks
        • Spoofing attacks
        • Phishing
    • Security in hardware
      • Tamper-proof and tamper-resistant designs
      • Embedded systems security
      • Hardware security implementation
        • Hardware-based security protocols
      • Hardware attacks and countermeasures
        • Malicious design modifications
        • Side-channel analysis and countermeasures
      • Hardware reverse engineering
    • Systems security
      • Operating systems security
        • Mobile platform security
        • Trusted computing
        • Virtualization and security
      • Browser security
      • Distributed systems security
      • Information flow control
      • Denial-of-service attacks
      • Firewalls
      • Vulnerability management
        • Penetration testing
        • Vulnerability scanners
      • File system security
    • Network security
      • Security protocols
      • Web protocol security
      • Mobile and wireless security
      • Denial-of-service attacks
      • Firewalls
    • Database and storage security
      • Data anonymization and sanitization
      • Management and querying of encrypted data
      • Information accountability and usage control
      • Database activity monitoring
    • Software and application security
      • Software security engineering
      • Web application security
      • Social network security and privacy
      • Domain-specific security and privacy architectures
      • Software reverse engineering
    • Human and societal aspects of security and privacy
      • Economics of security and privacy
      • Social aspects of security and privacy
      • Privacy protections
      • Usability in security and privacy
  10. Human-Centered Computing
    • Human computer interaction (HCI)
    • Interaction design
    • Collaborative and social computing
    • Ubiquitous and mobile computing
    • Visualization
    • Accessibility
  11. Applied Computing
    • Electronic commerce
    • Enterprise computing
    • Physical sciences and engineering
    • Life and medical sciences
    • Law, social and behavioral sciences
    • Computer forensics
    • Arts and humanities
    • Computers in other domains
    • Operations research
    • Education
    • Document management and text processing
  12. Social and Professional Topics
    • Professional topics
    • Computing / technology policy
    • User characteristics

Ref

美国科学信息研究所(Institute for Scientific Information,简称ISI)出版的一部世界著名的期刊文献检索工具,创建于1957年。凡是被该索引收录的期刊所刊登的论文,均成为SCI论文。

影响因子(Impact Factor, IF),某一期刊的文章在特定年份或时期被引用的频率,是衡量学术期刊影响力的一个重要指标。
影响因子 = 该刊前2年所发表的论文在第3年被引用的总次数 / 该刊前2年所发表的论文总数。

SCI分区 在中国,SCI有两种分区,一种是JCR分区,另一种是中科院分区。
JCR将收录期刊分为176个不同学科类别,每个学科分类按照期刊的影响因子高低,平均分为4个区:前25%(含25%)为Q1、位于25-50%(含50%)为Q2、位于50-75%(含75%)为Q3、位于75%之后为Q4
中科院首先将JCR中所有期刊分为数学、物理、化学、生物、地学、天文、工程技术、医学、环境科学、农林科学、社会科学、管理科学及综合性期刊13 大类。然后,将13大类期刊分各自为4个等级,即4个区。按照各类期刊影响因子划分,前5%为该类1区、6%~20%为2区、21%~50%为3区,其余的为4区。

分区差别

  1. JCR的Journal Ranking没有设置大类学科,只分为176个具体学科,也就是中科院分区表中所指的小类学科。
  2. JCR每个区含有该领域总量25%的期刊;中科院的分区如同社会阶层的金字塔结构,1区和2区杂志很少,杂志质量相对也高,基本都是本领域的顶级期刊。
  3. JCR是按本年度公布的IF进行分区,中科院是按期刊前3年IF的平均值进行分区。
  • 什么是核心期刊
  • 期刊来源数据库的大致排名
  • 什么是顶刊、权威期刊、核心A、核心B、核心C
  • JCR分区与中科院分区
  • 中科院2023年预警国际期刊 [SCI期刊分区/期刊名词 这都是什么意思? - 知之的文章 - 知乎]: https://zhuanlan.zhihu.com/p/108401297
  • ISSN
  • DOI
  • 他引率
  • 自引率
  1. 搜索导师名字并下载他发布的所有文献目录
    1. Aminer
  2. 根据文献目录下载文献原文
    1. 本校library上/open access/ 其它渠道
    2. sci-hub
    3. science digester
    4. SJR
    5. 文献部落
  3. 通过一篇文献找到关联的其它文献
    1. research rabbit
    2. connected paper
  4. 通过文献找到相对应的代码
    1. paper with code

不要盲从 CCF推荐国际学术会议和期刊 和 中科院分区 (尤其是后者) 。

摘自 CCF推荐国际学术会议和期刊

必须指出的是,本《目录》是CCF认为值得计算机界研究者们发表研究成果的一个推荐列表,其目的不是作为学术评价的 (唯一) 依据,而仅作为CCF的推荐建议供业界参考。还需要说明的是,由于领域的交叉和视角的差异,同一刊物/会议在不同领域存在认识上的差异是正常的,本列表也只代表了CCF对这些会议和刊物的推荐建议。此外,刊物和会议的影响力并不直接和发表在其上的单一论文的影响力发生联系,因此不建议任何单位将此《目录》简单作为学术评价的依据。如果由于将此《目录》作为学术评价的依据而引起纠纷,本学会不承担任何责任。

对于期刊,也不用特别在意影响因子 (Impact Factor, IF) ,比较热门的领域 (比如 AI) IF 就是比较高。 类似地,也不能单单用引用量来评价学者,热门领域文章比较多,引用量自然也比较多。


关于为什么中科院分区中频频出现离谱分区的讨论:

如何看待2019年发布的中国计算机学会(CCF)推荐国际学术会议和期刊目录? - 知乎

清华现在取消原本的毕业要求限制,就是希望学生多去做一些 solid work,别再水 sci (对于计算机学科) ,水 conference,真的做一些有意义的东西,让别人看了之后有 insight 那种,这才是博士该干的事情啊!

什么才算计算机的顶级会议? - 孙挺Sunt的回答 - 知乎

判断一个会议好不好,主要就是看这个方向的研究人员对它的评价如何。
至于 CCF 评级,这固然是个不错的标准,但毕竟也是由人评出来的,所以分级时肯定也考虑了各种现实因素,比如负责评选的人可能倾向于拔高自己经常灌的那些会议。
就像是你总不会认为 985、211 是完全按照学校水平分的吧?

因为我国掌控权力和资源的领导群体的意识形态,特别是对西方体系的认知,落后于国力发展。国家没有投入资源和精力去运作诺贝尔奖

任何奖项本质就是一场营销,都是可以运作和攻关的,并不代表真实的科学突破。

... (省略)

为什么现在中国高校还没拿这种专项经费去运作诺奖呢?1,还是敬畏之心没破除。2,之前中国的诺奖,因为种种原因,没有大规模宣传,没有对高校领导形成政绩压力,没有形成政绩锦标赛。

下面就看哪个高校领导先反应,去攻关瑞典皇家科学院了。因为诺奖里面没有数学,物化生和经济学,都吃硬件,吃平台,所以还是比较好运作的。

PS:但凡当年屠呦呦先生在诺贝尔奖演讲词里面,在致敬毛主席的时候,也致敬一下改开四十年和社会主义新时期,各个高校的政绩锦标赛早就搞起来了。现在诺奖至少有5个了。

这个奖跟奥运金牌,维也纳金色大厅,肖邦钢琴比赛,网球大满贯,没啥区别。

PS关于门捷列夫为什么没拿奖:

门捷列夫家族是油气寡头。这个寡头在高加索-里海-阿塞拜疆一带跟诺贝尔家族抢油井。激烈程度跟我国山西煤老板抢矿一样,黑白两道各种手段都用上了。以门捷列夫家族大获全胜而告终。那么,诺贝尔怎么会给门捷列夫发奖呢?所以,这个奖从一开始就是不纯粹的。

9 【为什么发出第一篇论文前你的观点不是很重要 - 爱学习的小语 | 小红书 - 你的生活兴趣社区】 😆 rhZEIlkfLErniNp 😆 https://www.xiaohongshu.com/discovery/item/68020269000000001d016913?source=webshare&xhsshare=pc_web&xsec_token=ABLOfWBRKgkPaxjeqZ-MGvaphri8Q-Vs38tX5WQGRQhoA=&xsec_source=pc_share