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. 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 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 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. 

Information about topics, submissions, and dates are reported in the Call for Papers.

primi sui motori con e-max