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KDWEB 2018
4th International Workshop on Knowledge Discovery on the Web
June 5h, 2018, Caceres (Spain)

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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 2018 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 2018 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 2018 will contribute to discuss and compare suitable novel solutions based on intelligent techniques and applied in realworld applications. The workshop is hosted by the 18th International Conference on Web Engineering (ICWE 2018).


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Topics of Interest
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KDWeb will contribute to propose innovative solutions in the following areas, but not limited to them:

Big Data
Data Mining
Deep Learning
Feature Selection and Extraction
Hierarchical Categorization
Information Filtering and Retrieval
Knowledge Discovery in BioInformatics
Linked Data
Machine Learning
Open Data
Recommender Systems
Semantic Web
Semantics and Ontology Engineering
Social Media
Social Media Measures
Text Categorization
Text Mining
Web Information Filtering and Retrieval
Web Mining
Web of Data
Web Personalization and Recommendation


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Important Dates
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Paper Submission: April 15, 2018 (Extended!)
Acceptance Notifications: April 28, 2018
Camera Ready: May 15, 2018
Workshop Day: June 5, 2018
Final Paper Camera Ready: July 5, 2018


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Submissions
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Authors should submit an original paper in English, carefully checked for correct grammar and spelling, using the on-line submission procedure. Authors could submit either regular papers or long abstracts. For the submission details click here. At least one author of each accepted paper must register for the conference and present the paper there.


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Organizers
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Workshop Chairs

Giuliano Armano (Department of Electrical and Electronic Engineering - University of Cagliari, Italy)
Matteo Cristani (Department of Computer Science - University of Verona, Italy)
Alessandro Giuliani (Department of Electrical and Electronic Engineering - University of Cagliari, Italy)
Álvaro Rubio-Largo (Universidade NOVA de Lisboa, Portugal)
Publication Chair

Alessandro Bozzon (Software and Computer Technology Department - Delft University of Technology, Netherlands)