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    KDWEB 2017 - 3rd International Workshop on Knowledge Discovery on the WEB

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    Website http://www.iascgroup.it/kdweb2017 | Want to Edit it Edit Freely

    Category Computer Science; Machine Learning; Knowledge Discovery

    Deadline: June 24, 2017 | Date: September 11, 2017-September 13, 2017

    Venue/Country: Cagliari, Italy

    Updated: 2017-03-20 19:26:56 (GMT+9)

    Call For Papers - CFP

    Nowadays data is created, shared, and stored at an impressive pace, as the world became more connected, networked, and traceable. In particular, data rapidly increased its scope and size, with the continuous growth in volume, variety, and velocity. Furthermore, data changed from static, complete, and centralized to dynamic, incomplete, and distributed, leading 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 growing 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 2017 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 2017 will contribute to discuss and compare suitable novel solutions based on intelligent techniques and applied in real-world applications.

    The KDWeb 2017 technical program will include a Special Session on Knowledge Discovery on BioInformatics. Its objective is to complement the regular program with new or emerging topics of particular interest to the bioinformatics community. The aim of a special session is to provide an overview of the state-of-the-art as well as to highlight current research directions and challenges in specific fields of bioinformatics.

    Submitted papers will be peer-reviewed by members of the Committee based on originality, significance, quality, and clarity.

    ***Posters/Demos***

    The KDWEB Poster and Demo Session is a forum to encourage interactions among researchers, practitioners, and master/PhD students. The session allows them to present their new and innovative work in-progress. Submitted posters or demos are expected to be aligned with one or more of the workshop relevant topics. Both poster and demo papers will be peer-reviewed by members of the Committee based on originality, significance, quality, and clarity. More details are provided in the KDWEB Poster and Demo CfP.

    ***Topics of Interest***

    Topics of interest will include (but not are limited to):

    - Big Data

    - Data Mining

    - Deep Learning

    - Feature Selection and Extraction

    - Hierarchical Categorization

    - Information Filtering and Retrieval

    - Knowledge Discovery on BioInformatics

    - Linked Data

    - Machine Learning

    - Open Data

    - Recommender Systems

    - Semantic Web

    - Semantics and Ontology Engineering

    - Social Media

    - Text Categorization

    - Text Mining

    - Web Information Filtering and Retrieval

    - Web Mining

    - Web of Data

    - Web Personalization and Recommendation

    ***Submissions***

    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.

    ***Important Dates***

    Regular Paper Submission: June 24, 2017

    Notification of Acceptance (Regular Papers): July 17, 2017

    Demos and posters submission deadline: August 1, 2017

    Notifications of acceptance (demos and posters papers): August 18, 2017

    Camera ready submissions: September 1, 2017

    Workshop Dates: September 11-13, 2017

    ***Organizers***

    - Giuliano Armano (Department of Electrical and Electronic Engineering - University of Cagliari, Italy)

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

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

    - Alessandro Giuliani (Department of Electrical and Electronic Engineering - University of Cagliari, Italy)

    For any further information, check the website (http://www.iascgroup.it/kdweb2017), or send

    an e-mail at the address: kdwebatiascgroup.it.


    Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
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