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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