Vol. 22 No. 1/2018
Issue Topic: Big Data
Saving Large Semantic Data in Cloud: A
Survey of the Main DBaaS Solutions
Bogdan IANCU, Tiberiu Marian GEORGESCU 5
In the last decades, the evolution of ICT has been spectacular,
having a major impact on all the other sectors of activity. New
technologies have emerged, coming up with solutions to existing problems
and opening up new opportunities. This article discusses solutions that
combine big data, semantic web and cloud computing technologies. The
authors analyze various possibilities of storing large volumes of data
in triplestore databases, which are currently the matter of choice for
storing semantic web data. The paper first presents the existing
solutions for installing triplestores on the premises and then focuses
on triplestores as DBaaS (in cloud). Comparative analyzes are made
between the various identified solutions. This paper provides useful
means for choosing the most appropriate database solution for semantic
web data representation, both on premises or as DBaaS.
Keywords: Big Data, Cloud computing, Semantic Web
Big Data in the Aerospace Industry
Victor Emmanuell BADEA, Alin ZAMFIROIU, Radu BONCEA 17
This paper presents the approaches related to the need for large
volume data analysis, Big Data, and also the information that the
beneficiaries of this analysis can interpret. Aerospace companies
understand better the challenges of Big Data than the rest of the
industries. Also, in this paper we describe a novel analytical system
that enables query processing and predictive analytics over streams of
large aviation data.
Keywords: Big Data, SAP - Predictive Maintenance,
Predictive Maintenance of Propulsion Systems for Aircraft, Big Data in
aerospace
The Power of Social Media Analytics: Text Analytics Based on Sentiment
Analysis and Word Clouds on R
Ahmed Imran KABIR, Ridoan KARIM, Shah NEWAZ, Muhammad Istiaque HOSSAIN
25
Apparently, word clouds have grown as a clear and appealing
illustration or visualization strategy in terms of text. Word clouds are
used as a part of various settings as a way to give a diagram by
cleansing text throughout those words that come up with most frequently.
Generally, this is performed constantly as an unadulterated text
outline. In any case, that there is a bigger capability to this basic
yet intense visualization worldview in text analytics. In this work, we
investigate the adequacy of word clouds for general text analysis
errands and also analyze the tweets to find out the sentiment and also
discuss the legal aspects of text mining. We used R software to pull
twitter data which depends altogether on word cloud as a visualization
technique and also with the help of positive and negative words to
determine the user sentiment. We indicate how this approach can be
viably used to explain text analysis tasks and assess it in a
qualitative user research.
Keywords: Big data, Text Analytics, Social Media
Analytics, R, Sentiment analysis, Word Cloud, Twitter Analysis
Student eXchange Process Modelling and Implementation by Using an
Integrated BMP-SOA Approach
Octavian DOSPINESCU, Catalin STRIMBEI, Roxana-Marina STRAINU, Alexandra
NISTOR 39
One of the key processes of an open University Information System
concerns managing the student exchange activities. In this paper we will
try to address the challenges regarding modelling and implementation
when integrating such a process by crossing different information
systems. Our approach will leverage SOA architecture by using BPM in
order to structure and build the service orchestration level.
Keywords: BPM, SOA, JAX-RS, Service Oriented
Architecture, RESTful Web Services
Students' Assessments about InfoStart Internship Program, in Economic
Informatics and Cybernetics
Adriana REVEIU, Ana Ramona BOLOGA 59
This paper provides an overview about the expectations and
assessment of students attending the internship program in Economic
Informatics and Cybernetics, developed within InfoStart program,
organized at the Faculty of Economic Informatics, Cybernetics and
Statistics, from Bucharest University of Economic Studies, Romania. 397
students accomplished 3 weeks internship stage, in May 2015, within
InfoStart program. In order to identify the expectations of the students
from the target group, a sociological survey has been conducted at the
beginning of InfoStart program. At the end of the internship program,
developed within the project, the attending students fulfilled
self-evaluation reports. So 397 completed self-evaluation reports have
been achieved and used to set up the analysis. The students' responses
reveal a very successful internship program in Economic Informatics and
Cybernetics, in term of program quality, program utility, students'
self-assessment behavior, and companies' employee behavior. The results
reveal that three internship factors, namely: a pleasant working
environment, good working infrastructure and proficient trainer, get
students overall satisfaction of the internship stage.
Keywords: Internship, Students' Assessment, Students'
Expectation
Identifying Business Models for Re-use of Cultural Objects by Using
Modern ICT Tools
Cristian CIUREA, Florin Gheorghe FILIP 68
In this paper is presented an economic model for revitalization of
cultural institutions with the help of modern information and
communication technologies tools and techniques. By revitalization of
cultural institutions we mean the increase in terms of public image,
visibility, number of visitors, and not lately, revenues. One of the
modern ICT techniques used in this situation is the implementation of
virtual exhibitions for promotion and valorization of cultural
collections and cultural heritage elements. There are already available
excellent ICT tools (one example to be described in the paper is MOVIO)
that are used to create virtual exhibitions, some of them being
implemented within cultural European projects.
Keywords: Business Model, Cultural Heritage,
Digitization, Revitalization, Virtual Exhibitions
Gender Statistical Analysis Applied for Identifying Style Patterns in
English Academic Writing
Madalina ZURINI 76
The present paper addresses the problem of writing style patterns in
the context of English Academic Writing. Stylometric analysis is used in
order to extract the main characteristics obtained from the evaluation
of articles written in well-known scientific journals such as Elsevier
and Springer. The objective of the paper is to establish a pattern
description of articles written in the same domain depending on the
gender of the authors. Relevant prior written work upon the current
subject reveal different characteristics of writing style of authors
from different cultural orientation and gender. The paper describes the
main characteristics taken into account for the clustering model when it
comes to title, abstract and chapters’ construction within the analyzed
articles. A short description of the algorithms and tools for clustering
and space reduction is presented for further selecting the best
combination for the proposed model. An additional statistical layer is
added to the current clustering algorithms and space reduction for
obtaining statistical proven results of usage. An aggregated structure
model is conducted as a result of characteristics selection and
processing for future work usage in gender analysis of scientific
articles writing. Conclusions and withdrawn along with the future
directions extracted from the current work. A database structure is
proposed formed out of statistical calculated percentage of papers
depending on the author gender. The relevance of the work can be well
used as a guide line in writing scientific articles as the main musts in
scientific writing are presented.
Keywords: Stylometry, Gender analysis, Clustering
algorithms, Space reduction, Feature selection
Book Review: The Programmer Career
Catalin BOJA 85
The 17th International Conference on Informatics in Economy, IE 2018 87
The 11th International Conference on Information Technology and
Communications Security, SECITC 2018 88
Publishing Guide for Authors 89
INFOREC Association 91
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