Journal of Web Semantics

Journal of Web Semantics 由 Elsevier 出版，属中科院计算机科学大类（2025 升级版3区）。按 OpenAlex 近年发文统计，该刊主要发表 Semantic Web and Ontologies、Service-Oriented Architecture and Web Services、Biomedical Text Mining and Ontologies 等主题的论文，这 3 个主题约占 40.3%，主导子领域为 Artificial Intelligence。（根据 OpenAlex 主题统计与中科院分区数据生成）

The Journal of Web Semantics (JWS) is an interdisciplinary forum at the intersection of the Semantic Web, Knowledge Graphs (KGs), and Artificial Intelligence (AI), with a strong emphasis on both theoretical and applied research. Building on its foundation as a venue for exploring knowledge-intensive and intelligent Web technologies, JWS recognizes the pivotal role that KGs and Semantic Web (SW) technologies play in the evolving AI landscape, particularly amid recent breakthroughs in Generative AI, neuro-symbolic systems, and autonomous agents.JWS seeks to capture the critical convergence between symbolic and statistical approaches to AI, focusing on the methods, architectures, and foundational theories that drive the integration of Semantic Web and KG technologies with machine learning, deep learning, Large Language Models (LLMs), and other AI techniques. The journal encourages contributions that not only demonstrate impactful applications but also advance the theoretical understanding of how structured, semantic knowledge can enhance intelligent systems.We welcome high-quality submissions that include, but are not limited to, the following areas:Theoretical Foundations and Methodological AdvancesFormal Models and Representations: New theoretical frameworks and formalisms for KGs, ontologies, reasoning, and semantic data management, including studies on expressivity, consistency, change management, and evolution in complex or dynamic systems.Hybrid and Neuro-Symbolic Architectures: Methodological insights into combining symbolic knowledge representation with sub-symbolic learning, including formal characterizations of neuro-symbolic systems and architectures.KG-AI Integration Methods: Novel algorithms and frameworks that tightly couple KGs with AI methods in ways that yield results unattainable by either approach alone, including Logic Augmented Generation and reasoning-enhanced learning.Evaluation and Benchmarking: Research on robust evaluation methodologies for KG-AI systems, with attention to correctness, scalability, data quality, reliability, interpretability, and accountability. Applied and Interdisciplinary ResearchCross-Disciplinary Studies: Integrative work drawing from ontology engineering, databases, NLP, machine learning, human-computer interaction, and cognitive science, among others, with clear theoretical or methodological contributions.Domain Applications: Real-world use cases showing how KGs and SW technologies enable or enhance AI in specific domains: Healthcare and Life Sciences, Education, Legal Tech, Scientific Discovery, Smart Cities, Industry, Finance, Cultural Heritage, Art and Creativity, etc.Engineering, Resources, and System IntegrationKG Engineering Automation: AI-driven approaches to the (semi-)automatic creation, population, alignment, and refinement of KGs and ontologies, especially using LLMs and foundation models.System Descriptions and Architectures: Descriptions of integrated KG-AI systems, with technical insights into issues such as hallucination mitigation, knowledge retrieval, cross-modal integration, and interaction design.Auditing, Explanation, and Governance: Research on how KGs contribute to transparency, robustness, and auditability of AI systems, including formal representation of workflows, provenance, and ethical constraints.Data and Knowledge Resources: Descriptions of high-impact ontologies, datasets, benchmarks, and tools that enable research or deployment in SW/AI integration. JWS is especially interested in papers that address current and future challenges in the field, including:Modelling expressivity for complex systemsKnowledge engineering automationIntegration of heterogeneous data and knowledge sourcesScalable, efficient reasoning with large-scale KGsAccessibility and usability of semantic systemsProvenance, privacy, and interoperability in AI-KG ecosystemsSocietal impacts, costs, risks, and sustainability of KG-based AIEvaluation of semantic methods and systems Finally,

摘自期刊官网 Aims & Scope

研究方向（LetPub）：工程技术-计算机：人工智能

主编 Valentina Presutti出版商官网

编委会国家分布：中国大陆 3 位（约 3%）；主要国家 德国 22、意大利 19、英国 16、美国 12、法国 7（共 110 位编委标注了国家） 编委会 ↗出版商官网 · 2026-10-01

中科院期刊分区表

数据库收录

SCIEScopusDOAJLetPub

国际期刊预警名单：各版本均未列入LetPub

不同版本、大类与小类分别展示，不将不同评价口径合并为一个分区值；投稿与考核前请确认所在机构采用的版本。

影响力指标

影响因子

3.08LetPub · 2026-09-13

影响因子（出版商公布）

3.2出版商官网 · 2026-10-01

CiteScore 2026-06

10.2LetPub · 2026-09-13

CiteScore（出版商公布）

10.2出版商官网 · 2026-10-01

SJR 2026-06

1.01LetPub · 2026-09-13

SNIP 2026-06

2.35LetPub · 2026-09-13

h-index

74LetPub · 2026-09-13

h-index

103OpenAlex · 2026-10-01

i10-index

478OpenAlex · 2026-10-01

两年平均被引

8.76OpenAlex · 2026-10-01

自引率

3.1%LetPub · 2026-09-13

Gold OA 文章占比

78.33%LetPub · 2026-09-13

发文规模

年文章数

20LetPub · 2026-09-13

不同来源的统计口径与观测时间不同，页面保留各来源原值；“出版商公布”为期刊官网自述数据。

各来源数据

平均审稿速度（社区反馈）

>12周，或约稿来源Elsevier官网：平均14.6周LetPub · 2026-09-13

平均录用比例（社区反馈）

容易LetPub · 2026-09-13

投稿到首次决定

68 天出版商官网 · 2026-10-01

外审后首次决定

255 天出版商官网 · 2026-10-01

投稿到接收

347 天出版商官网 · 2026-10-01

接收到发表

11 天出版商官网 · 2026-10-01

投稿到发表（期刊自报）

约 21 周DOAJ · 2026-10-11

评审方式

单盲同行评审DOAJ

社区反馈来自投稿者样本，置信度 0.5，不代表期刊承诺；“出版商公布”的时间节点定义以官网为准。

• APC 费用说明 ↗DOAJ
• 费用减免政策 ↗DOAJ
• 开放获取声明 ↗DOAJ
• 许可与版权 ↗DOAJ

费用以期刊官网为准；不同来源的观测时间可能不同，页面保留各来源原值，不做平均。

摘录来自期刊官网页面，仅保留原文片段；“模型摘要”由 Workers AI 生成并经原文校验，以官网为准。

出版商

Elsevier

出版国家或地区

NETHERLANDS

出版语言

English

出版周期

Quarterly

创刊年份

2003

ISSN

1570-8268

电子版 ISSN

1873-7749

官方链接

• 期刊主页 ↗DOAJ
• 投稿系统 ↗出版商官网
• 作者指南 ↗DOAJ
• Aims & Scope ↗DOAJ
• 专刊 / 特刊征稿 ↗出版商官网
• APC 费用说明 ↗DOAJ
• 费用减免政策 ↗DOAJ
• 开放获取声明 ↗DOAJ
• 许可与版权 ↗DOAJ
• 评审流程 ↗DOAJ
• 编委会 ↗DOAJ
• 查重政策 ↗DOAJ