会议信息

WebDB 2018: International Workshop on the Web and Databases

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截稿日期:
2018-02-09 已截稿
通知日期:
2018-03-14
会议日期:
2018-06-10
会议地点:
Houston, Texas, USA
届数:
21
CCF: C   QUALIS: B1   浏览: 59818   关注: 41   参加: 4
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会伴指数 (CP-I)

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学术认可 (35%)
78
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83
社区关注 (10%)
51
资料公开度 (15%)
25

用到的输入: 收录等级：CCF C, QUALIS B1 · 有据可查的届次：21 · 在会伴关注它的研究者：41 人 · 过去 24 个月打开过本页的研究者：6 人

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置信度 80% —— 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 1.2 · 算于 2026-10-23

征稿

WebDB 2018 (International Workshop on the Web and Databases) is a CCF C / QUALIS B1 conference held in Houston, Texas, USA on 2018-06-10. The paper submission deadline is 2018-02-09. Acceptance notifications are sent on 2018-03-14.

The Web is an ever-evolving source of information, with data and knowledge derived from the Web powering a great range of modern applications. Accompanying the huge wealth of information, Web data also introduces numerous challenges due to its size, diversity, volatility, inaccuracy, and contradictions. WebDB, first held in 1998, provides a forum for researchers, theoreticians, and practitioners to share and promote insights, ideas, and novel research directions for the management of Web data. It covers a broad range of topics, including the extraction of knowledge from the Web, the transformation, generation, dissemination, and exchange of Web data, functionality pertaining to interfaces and applications, and many others. We aim to bring together the research efforts from both the academia and industry, and we solicit papers on a broad range of research topics, types and methodologies in computer science, such as on applications and tools, systems, user experience and interface, and theoretical foundations and/or analysis. WebDB has taken place twenty times already, has had a high impact, and has published and provided the forum for a substantial amount of seminal research. The theme of this year's workshop is Web data for ML - ML for Web data. This theme emphasizes the cross-disciplinary challenges and opportunities that arise with Web data. On one hand, a large portion of Web data fuels ML, with novel applications such as predictive analytics, Q&A chat bots, and content generation. On the other hand, the new wave of ML technology found its way into traditional Web data challenges, with contributions such as web data extraction with deep learning, data cleaning, and even using ML to optimize data processing pipelines. Submissions relevant to the theme are particularly encouraged, but WebDB will also publish works more generally pertaining to Web data management.
由 Shuang Li 最后更新于

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