Alex Becheru

Tourist review analytics using complex networks

A number of techniques for Natural Language Processing (shortly, NLP) based on graph representations were developed. Usually they target a specific NLP task, such as: text summarisation, syntactic parsing, word sense disambiguation, ontology construction, sentiment and subjectivity analysis, or text clustering. In this paper we explore complex network representation of tourist reviews for extracting lexical and quantitative features of the review text. The most important contribution of our proposal consists of defining a new method for keywords extraction using Complex Network ranking metrics.

Polarity shifting for Romanian sentiment classification

There are three main classes of modifiers that can affect the polarity of the sentiments described in natural language texts: negations, intensifiers and diminishers. In this paper, we concentrate on the study of these particular words which have a very important semantic role in any natural language description. Our study is applied on a real data set extracted from the popular Romanian Web site AmFostAcolo dedicated to tourist impressions.

Initial evaluation of an ontology for transport brokering

Currently there is a lot of interest in developing applications to support the mobility and movement of resources and related features. One notable example is freight transportation management. Ontology-driven multi-agent systems are promising technologies for building systems that provide an intelligent service for freight transportation brokering aiming to create optimal transport policies such that transport costs are reduced to the minimum. We propose a freight transportation ontology and then we define a scenario of transport logistics to validate our proposed ontology. The evaluation is based on the careful examination of ontology concepts and properties that are required for capturing freight transportation requests and resources.

Towards Social Data Analytics for Smart Tourism: A Network Science Perspective

In this paper we present our preliminary results regarding collecting, processing and visualizing relations between the user comments that were posted on Smart Tourism Web sites. The focus of this paper is on investigating the user interactions generated by expressing questions and answers containing the users’ impressions and opinions about the attractions offered by various tourism destinations. We propose a prototype system based on the design of a conceptual data model and of the development of a data processing workflow that allows to capture, to analyze and to query the implicit social network that was determined by the relations between user comments, using specialized software tools for graph databases and complex networks analytics.

Complex Networks’ Analysis Using an Ontology-Based Approach: Initial Steps

This paper presents a new ontology that enables the knowledge-based analysis of complex networks. The purpose of our research was to develop a new approach for the knowledge-based analysis of complex networks based on various network attributes and metrics. Our approach is both easy to use and easy to understand by a human. It facilitates the automated classification of different types of networks. For the creation of this ontology we applied an already known methodology from the scientific literature. The ontology was also enriched with our own developed methods. We applied our ontology to the analysis scenarios of complex networks obtained from real world problems, thus supporting its generality, as well as its usability across domains.

Analyzing students’ collaboration patterns in a social learning environment using StudentViz platform

Understanding students’ collaboration patterns is an important goal for teachers, who can thus obtain an insight into the collaborative learning process. Social network analysis and network visualizations are commonly used for exploring social interactions between learners. However, most existing network visualization platforms are deemed too complex by the teachers, who do not possess social network analysis expertise. Therefore, we propose an easy to use platform for visualizing students’ collaboration patterns, called StudentViz. An overview of the tool, including a description of its implementation and functionalities, is provided in the paper. An illustration of how the tool can be used in practice, for investigating students’ collaboration patterns in a social learning environment, is also included.

StudentViz: A Tool for Visualizing Students’ Collaborations in a Social Learning Environment

Visualizations play an important role in learning analytics, supporting reflection and decision making. Network representations are commonly used for depicting social interactions between learners. While there are many network visualization platforms available, most of them are aimed at researchers, requiring social network analysis expertise. Our goal is to provide a simple tool for visualizing students’ collaboration patterns in a social learning environment, which should be easy to use by the teacher. The paper presents a description of this tool (called StudentViz), some design and implementation details, and an illustration of its functionalities. It further shows that the tool adequately addresses the visualization needs of the instructors, fostering insight gaining.

Semantic aspect derivation of the Praxème methodology from the elaborate lexicon extended language

This paper treats the representation of the intentional aspect of the Praxème methodology in the elaborate lexicon extended language with a conceptual view, noted eLEL, facilitates automatic derivation into semantic aspect of this methodology. Because it is the terminology database, brings together the specific terms used by the enterprise, and has a UML metamodel, which enables to properly satisfy this derivation. In this case, the eLEL as the intentional aspect becomes the initial phase of Praxème. Therefore, our strategy is to use eLEL models to automatically derive the semantic aspect of Praxème. To do this, we will establish rules for deriving eLEL models of class diagrams and UML state machine. These rules are then translated into ATL code to obtain UML diagrams in XMI format. In turn, the UML diagrams in XMI format will be transformed to obtain the concrete UML diagrams. Then, the results of this derivation process are UML diagrams in Ecore and XMI format and concrete UML diagrams that are components of the semantic aspect of the Praxème methodology. In short, our method proposes the derivation of UML class diagram from natural language. Finally, we tested our approach on a case study by comparing it with two other approaches, different from our own. The results shows that our method is useful to stakeholders, as it can bring about a complete and exact software specification in a very short time.

Complex Network Analysis of a Tourism Content Sharing Network

This paper presents results of the analysis of a tourism information Web-site (AmFostAcolo.ro) by using Complex Networks (CN) methods. The work accomplished here complements a previous paper, where we discussed data extraction and modelling into a complex network. Properties of the resulted network, communities and vertices are looked upon, in order to extract useful information and detect social phenomena. Temporal analysis methods are employed for examining the evolution of the web-site. The results obtained prove the natural development of the Web-site and the usefulness of CN analysis methods in this scenario.

Organisational Network Analysis within the academic world: Initial steps

Organisational Network Analysis (ONA) is a branch of Complex Networks science that has the purpose to inspect and evaluate the exchange of information within organisations. Although many studies have been conducted using ONA on different types of organisations, we are not aware of any papers that regard higher education organisations. This papers goal is to evaluate how well information is exchanged within a small size university, the Romanian-German University of Sibiu. In order to better assess the organisation we retrieved data from 3 sources: email logs, organisational chart and directly from the employees. Another scope of this study is to determine which of the above mentioned sources give reliable analysis on information flow between university staff.