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Knowledge Discovery
on the Web

May 20, 2021, Biarritz, France

Submit Paper

7th International Workshop on Knowledge Discovery on the Web

Knowledge Discovery is an interdisciplinary area focusing upon methodologies for identifying valid, novel, potentially useful and meaningful patterns from such 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 entailed that Knowledge Discovery approaches focused on the World Wide Web (WWW), whose popular use as global information system led to a huge amount of digital data. KDWeb 2021 is focused on the field of Knowledge Discovery from digital data, with particular attention for Data Mining, Machine Learning, and Information Retrieval methods, systems, and applications. KDWeb 2020 is aimed at providing a venue to researchers, scientists, students, and practitioners involved in the fields of Knowledge Discovery on Data Mining, Information Retrieval, and Semantic Web, for presenting and discussing novel and emerging ideas. KDWeb 2021 will contribute to discuss and compare suitable novel solutions based on intelligent techniques and applied in real-world applications. The workshop is hosted by the 21th International Conference on Web Engineering (ICWE 2021). For more information see the Call for Papers

18-21 May 2021
KDWEB
Workshop
and Conference
27th February 2021
Submission
Submission deadline
19th April 2021
Notification

Notification of acceptance

Workshop Details

 

In the current era of digital and social data, the world became more connected, networked, and traceable, with the consequent exponentially growth of data creation, sharing, and storing. In particular, data changed from static, complete, and centralized to dynamic, incomplete, and distributed; furthermore, data rapidly increased its scope and size, with the continuous increase of volumes, varieties, and velocities. All these aspects led to new challenges undertaken by the field of Big Data Analysis. Consequently, there is the need for novel computational techniques and tools able to assist humans in extracting useful information (knowledge) from the huge volumes of data. Knowledge Discovery is an interdisciplinary area focusing upon methodologies for identifying valid, novel, potentially useful and meaningful patterns from such data, and is currently widespread in numerous fields, including science, engineering, healthcare, business, and medicine. A major aspect of Knowledge Discovery is to extract valuable knowledge and information from data. Typical tasks are aimed at gathering only relevant information from digital data (e.g., text documents, multimedia files, or webpages), by searching for information within documents and for metadata about documents, as well as searching relational databases and the Web.

Recently, the rapid growth of social networks and online services entailed that Knowledge Discovery approaches focused on the World Wide Web (WWW), whose popular use as global information system led to a huge amount of digital data. Typically, a webpage has unstructured or semi-structured textual content, leading to present to users both relevant and irrelevant information. Hence, there is the need of novel techniques and systems able to easily extract information and knowledge from the huge web data.

KDWeb 2021 is aimed at providing a venue to researchers, scientists, students, and practitioners involved in the fields of Knowledge Discovery on Data Mining, Information Retrieval, and Semantic Web, for presenting and discussing novel and emerging ideas. KDWeb 2021 will contribute to discuss and compare suitable novel solutions based on intelligent techniques and applied in real-world applications.

 

The workshop welcomes submissions of fresh investigations concerning experimental and applied studies on web Knowledge Discovery. The topics include but are not limited to:

 
Big Data on the Web
 
Data Mining
 
Deep Learning on the Web
 
Feature Selection and Extraction of Web data
 
Hierarchical Categorization of Web data
 
Knowledge Discovery
 
Linked Web Data
 
Machine Learning applications on the Web
 
Open Web Data
 
Semantic Web
 
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
 
Giuliano Armano

(Department of Mathematics and Computer Science -University of Cagliari, Italy)

 
Matteo Cristani

(Department of Computer Science -University of Verona, Italy)

 
Claudio Tomazzoli

(CITERA Interdepartmental Centre, Sapienza University of Rome, Italy)

Program

Schedule Content
To be announced

Location

Submissions

Authors should submit an original paper in English, carefully checked for correct grammar and spelling, using the on-line submission procedure. A submission can be up to 12 pages long, otherwise it will be rejected without review. Submissions will have a peer review by the program committee on the basis of technical quality, relevance to the workshop topics, originality, significance, and clarity. Please check the paper formats page so you may be aware of the accepted paper page limits. Authors will be informed about the type of acceptance regarding their submissions. Please check and carefully follow the instructions and templates provided. Each paper should clearly indicate the nature of its technical/scientific contribution, and the problems, domains or environments to which it is applicable. Papers that are out of the workshop scope or contain any form of plagiarism will be rejected without reviews. Submissions (and camera-ready) should be made in pdf; Latex formatting is highly recommended (Latex template is available here). To submit a paper please go to the Easy Chair system. The web submission procedure automatically sends an acknowledgment, by e-mail, to the contact author. After the reviewing process is completed, the contact author (the author who submits the paper) of each paper will be notified of the result, by e-mail. The authors are required to follow the reviews in order to improve their paper before the camera-ready submission. Submitting a paper means that, if the paper is accepted, at least one author should register and attend the workshop to present the paper.

Publications

As for the previous edition of KDWeb, a subset of accepted papers will be selected for being extended and published in a special issue of scientific journals. More info will be available as soon as possible. For the sake of knowledge, selected papers of KDWeb 2019 have been published in a special issue of Information (ISSN 2078-2489), see here for more info.