Participants intending to present a talk are invited to submit an abstract. All abstracts will undergo a reviewing process. Accepted abstracts will be distributed to the conference participants.
To submit your paper, please register via the link: https://www.conftool.net/ecda2017/
Guidelines for the abstract:
The pdf must be written in English and must not exceed one page. There are no specified guidelines for the abstract submission although takes care of title, author(s), affiliation(s), references, and 3–5 keywords. Participants are expected to enter the text directly via the conftool interface and submit a pdf format file with exact same text.
All authors of accepted abstracts are invited to submit full papers. Please note that all full papers will undergo a reviewing process. Accepted papers will be published in special volume of Archives of Data Science. Selected best papers will be published in special volume of ADAC or Agrumenta Oeconomica. We advise all authors interested to contribute to pay attention to the mandatory deadlines.
The broad range of relevant topics is illustrated by the following list of intended sections. Contributed papers from scholars and practitioners are invited on any of these as well as on related topics:
- Theory and Methods, including but not limited to Multivariate Methods, Exploratory Data Analysis, Clustering and Classification, Pattern Recognition and Machine Learning, Visualization and Scaling Methods, Evaluation of Methods
- Data Science, including Data Pre-Processing, Text and Web Mining, Information Extraction and Retrieval, Personalization and Intelligent Agents
- Applications, involving Marketing and Management Science, Banking and Finance, Production, Controlling and OR, Biostatistics and Bioinformatics, Genome and DNA Analysis, Medical and Health Sciences, Archaeology and Geography, Linguistics and Statistical Musicology, Psychology and Education, Library Science
- The Workshop on Library and Information Science solicits contributions on the role of classification and data analysis in this domain. Topics in this area include but are not limited to: Classification and subject indexing in the context of catalogs and resource discovery systems; Methods, approaches and applications in subject indexing, classification and data analysis in different countries; Open access to classification systems: How can we provide a sustainable classification infrastructure?; Linked (subject) data (e.g. faceted classification and linked data architectures: A happy alignment?); Classification, subject indexing and the semantic web (e.g. taxonomies and semantic web ontologies: How closely are they related to each other?); Automatic and manual methods in classification and subject indexing (e.g. mappings, concordances, heuristics); Subject retrieval in multilingual, multicultural environments; Serendipity in library collections and digital libraries
More information will be available soon.