Special Issue "Knowledge Discovery on the Web"
Deadline for manuscript submissions: closed (31 January 2020).
Interests: artificial intelligence; knowledge discovery; information retrieval
Interests: artificial intelligence; knowledge discovery; automated reasoning; social networks
Following the workshop KDWEB 2019 at ICWE, we propose a Special Issue of Information.
Knowledge discovery is an interdisciplinary area focusing upon methodologies for identifying valid, novel, potentially useful, and meaningful patterns from data, and currently is widespread in numerous fields, including science, engineering, healthcare, business, and medicine. Recently, the rapid growth of social networks and online services has entailed that knowledge discovery approaches focus on the World Wide Web (WWW), whose popular use as a global information system has led to a huge amount of digital data.
KDWeb 2019 focused on the field of knowledge discovery from digital data, paying particular attention to data mining, machine learning, and information retrieval methods, systems, and applications. KDWeb 2019 aimed to provide a venue to researchers, scientists, students, and practitioners involved in the fields of knowledge discovery on data mining, information retrieval, and the semantic Web, for presenting and discussing novel and emerging ideas. KDWeb 2019 will contribute to discussing and comparing suitable novel solutions based on intelligent techniques applied in real-world applications.
Topics of Interest
The workshop has been accepting submissions of fresh investigations concerning experimental and applied studies on Web knowledge discovery. Topics include but are not limited to the following:
Big data on the Web;
Deep learning on the Web;
Feature selection and the extraction of Web data;
Hierarchical categorization of Web data;
Linked Web data;
Machine learning applications on the Web;
Open Web data;
Semantics and ontology engineering for Web applications;
Social media mining;
Social media measures and applications;
Text categorization on the Web;
Text mining for Web applications;
Web data mining;
Web information filtering and retrieval;
Web personalization and recommendation.
Dr. Giuliano Armano
Dr. Matteo Cristani
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.
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