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Dear Readers,
Welcome to the 6th regular issue in 2017 with three high quality
regular papers and two papers from the focused topic "Recommender
systems and social network analysis".
As always, I'd like to thank all reviewers for their support and
efforts during the evaluation process of the articles. Furthermore,
I'd particularly like to acknowledge the generous support of the
members of the J.UCS consortium which enables us to continue to offer
J.UCS as an open content journal without publication fees.
In regular issue, I am very glad to introduce three accepted high
quality papers from authors from three different countries.
Mario Bravetti from Italy and France proposes in his paper a
middleware based on client-server protocols and on a set primitives, for managing resources and executing programs in Web Operating
Systems, which is based on an extension of the REST
architecture. Julia Kasch, Peter van Rosmalen and Marco Kalz from The
Netherlands discuss their work on a framework supporting educational
scalability, in particular assessment and feedback, applied for Open
Online Courses. Andre Rodrigues Oliveira, Ulisses Dias and Zanoni Dias
from Brazil report their research about a polynomial-time
approximation algorithm for the Sorting by Reversals and
Trasponsitions Problem.
In their guest editorial, the editors of the focused topic, Alexander
Felfernig from Graz University of Technology, Austria, Ralf Klamma
from RWTH Aachen, Germany, Tobias Ley from Tallinn University,
Estonia, and Dominik Kowald, Elisabeth Lex and Viktoria
Pammer-Schindler from Graz University of Technology & Know-Center,
Austria, write:
"The papers in this focused topic are invited extensions of papers
presented at the Workshop on Recommender Systems and Big Data
Analytics (RS-BDA 2016), co-located with the i-Know 2017, the
International Conference on Knowledge Technologies and Data-driven
Business. The i-Know conference series aims at advancing research at
the intersection of disciplines such as Knowledge Discovery,
Semantics, Information Visualization, Visual Analytics, Social
(Semantic) and Ubiquitous Computing. The goal of integrating these
approaches is to augment human intelligence by designing tools and
services, which interact naturally with humans, learn from their
experiences and generate and evaluate evidence-based hypotheses.
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The articles specifically deal with research from the fields of
recommender systems and social network analysis. Specifically, the
paper written by Mohsen Shahriari, Sabrina Haefele and Ralf Klamma
from RWTH Aachen in Germany addresses the use of recommendations to
identify overlapping communities in Online collaboration systems. By
using term frequency of words generated by users and combining them
with an extended clustering technique, the authors propose an
algorithm, which could be useful in question & answer forums to
suggest missing links between users. The second article written by
Rebekka Alm from Fraunhofer IGD Rockstock in Germany, however,
demonstrates the use of recommendations to foster information exchange
in production. The author proposes a framework that uses annotations
in combination with a formalized knowledge base to represent working
domains and illustrate the usefulness of this approach via the example
of an assembly assistance system."
Enjoy reading!
Cordially,
Christian Gütl, Managing Editor
Graz University of Technology, Graz, Austria
Email: cguetl@iicm.edu
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