Francesco Pascale

A Mobile Context-Aware Information System to Support Tourism Events

The experience of a touristic visit is a learning process very fascinating and interesting: the emotions can change according to the interests of the individuals, as well as of the physical, personal and social-cultural context. Applications for a mobile environment should take advantage of contextual information, such as position, to offer greater services to the user.

An Ontological Digital Storytelling to Enrich Tourist Destinations and Attractions with a Mobile Tailored Story.

Storytelling has evolved over the years: its ability to enchant, transform and persuade makes it a formidable mean, malleable and customizable, but not easy to use. The use of new technologies allowing it to reach a far greater level of effectiveness: the audience can join in the storytelling process, thus impacting positively on engagement and facilitating the development of long lasting relationships.

A context aware approach for promoting tourism events: The case of artist's lights in Salerno

This paper introduces a Context Aware App for the tourism. This app is based on a graphical formalism for the context representation: the Context Dimension Tree. The aim is to propose a Context Aware approach that acts as dynamic support for the tourists, equipped of a mobile device which reacts to a change of context adapting user interface, according to his/her current position and global profile. For example, the system can guide the tourist in the discovery of a town proposing him/her events mainly interesting for the user. A case study applied to a Christmas event in Salerno, an Italian town, has been analyzed considering various users (Italian tourists, foreign tourists, etc.) and an experimental campaign has been conducted, obtaining interesting

E-learning and sentiment analysis: a case study

E-Learning is becoming one of the most effective training approaches. In particular, the blended learning is considered a useful methodology for supporting and understanding students and their learning issues. Thanks to e-Learning platforms and their collaborative tools, students can interact with other students and share doubts on certain topics. However, teachers often remain outside of this process and do not understand the learning problems that are in their classrooms. A solution for ensuring the privacy of communication among students could be the adoption of a Sentiment Analysis methodology for the detection of the classroom mood during the learning process. In this paper, we investigate the adoption of a probabilistic approach based on the Latent Dirichlet Allocation (LDA) as Sentiment Grabber. The proposed approach can detect the mood of students on the various topics and teacher can better tune his/her teaching approach. The proposed method has been tested in real cases with effective and satisfactory results.

A Tailor made System for providing Personalized Services

Today, the existing technologies, such as smartphone and other pervasive devices, can be used for context awareness and help people to undertake conscious choices. In fact, unlike what happened in the past, all of these data are managed and contextualized for the particular application. We need to understand, select, treat and finally opportunely expose these data. In this scenario, there are many Context Aware applications. This paper introduces a tailor made system for providing personalized services and it is based on a graphical formalism for the context representation: the Context Dimension Tree. This system provides the needed information about places that are of great interest for the visitors, selecting them using user preferences. A case study is applied to an event in Salerno, an Italian town, called Artist’s Lights. Finally, an experimental campaign has been conducted, obtaining interesting results. Keywords—Context-Aware Computing, E-Citizenship,

BotWheels: a Petri Net based Chatbot for Recommending Tires.

Technological progress seems unstoppable: large companies are ready to implement more and more sophisticate solution to improve their productivity. The near future may be represented by so-called Chatbot, already present in the instant messaging platforms and destined to become more and more popular. This paper presents the realization of a prototype of a conversational workflow for a Chatbot in tires domain. The initial purpose has focused on the design of the specific model to manage communication and propose the most suitable tires for users. For this aim, it has been used the Petri Net. Finally, after the implementation of the designed model, experimental campaign was conducted in order to demonstrate its enforceability and

A Multilevel Graph Approach for Road Accidents Data Interpretation

Nowadays, due to the massive low-cost technology and mobile devices spread, our society is increasingly projected towards data production. Often, we find ourselves surrounded by data that, however, does not always lead to the knowledge, or toward information that we need. This is liable to eclipse the desire to use this data trying to predict the future. So much has been done in literature in regard to the extraction of information and interpretation of these data. However, in this field does not seem to be present a universal methodology for solving the problem, leading us to research new approaches more customized on the available dataset. The aim of this paper is to introduce an approach for the interpretation of data from sensors located within a city using three graphical views: Context Dimension Tree, Ontologies and Bayesian Networks. Through the Ontologies and the Context Dimension Tree it is possible to analyze the scenario from a syntactic and semantic point of view, assisting the construction of the he Bayes network structure that allow to estimate the probability that some events happen. A first preliminary analysis conducted on a London borough seems to confirm the effectiveness of the proposed method.

Chatbot: An Education Support System for Student

In the last few years there has been a fast growing up of the use of Chatbots in various fields, such as Health Care, Marketing, Educational, Supporting Systems, Cultural Heritage, Entertainment and many others. This paper presents the realization of a prototype of a Chatbot in educational domain: the purpose has focused on the design of the specific architecture, model to manage communication and furnish the right answers to the student. For this aim, it has been realized a system that can detect the questions and thanks to the use of natural language processing techniques and the ontologies of domain, gives the answers to student. Finally, after the implementation of the designed model, experimental campaign was conducted in order to demonstrate its utility.

A Conversational Workflow Model for Chatbot.

Extended Abstract—This paper presents the realization of a prototype of a conversational workflow for a Chatbot in tires domain. The initial purpose has focused on the design of the specific model to manage communication and propose the most suitable tires for users. For this aim, it has been used the Petri Net. Finally, after the implementation of the designed model, experimental campaign was conducted in order to demonstrate its enforceability and efficiency. In research fields, the issue of Chatbot and Bot in general has been discussed for many years, although it has seen an increasingly gradual slowdown in recent years. In fact, the amount of investment by companies in trying to create a Bot as similar to an operator is growing[1][2]. The main aim of this paper is to describe a software module prototype, called workflow manager, who is responsible for the management of the flow of conversation between a Chatbot and a user, applied at a real case. Our case study concerns a Chatbot, which will serve for help the choice of tires to buy. After an analysis on the state of art, we have realized the general pattern of operation of the bot and then using the Petri Nets, we have realized the workflow model. Finally, it was conducted the experimental phase that has highlighted the strengths and weaknesses points of the Bot. In the next section, the related works are presented. The design of Workflow Manager was divided in two phases: in the first place, is provided the design of model able to explicitly describe and represent the considered knowledge domain (tires). In the second place, the purpose is to define a workflow module. Therefore, the first aim has been to build an ontology to describe the reference taxonomy. The advantage of this approach is to be able to represent concepts, properties, attributes and constraints of the one part and of the other part a reference model for the workflow[3][4]. In this work, it can be considered the child pneumatic concept. It has several children including the vehicle node, whose descendants are the cars and motorcycles node, and the node size. Each of these nodes presents, in turn, determined descendants. A choice of this type of structure has been effected because, generally, to find a specific pneumatic, must be indicated in detail the characteristics of the vehicle or the size of the eraser. Then, the ontology allows achieving a knowledge and the links between concepts (for example, we can see that we have various types of vehicles or that the concept of car is made up of the attributes of the brand, model, version and year). The next goal was to provide a reasoner that can access in a reference ontology and that it was able to generate and follow a consistent and efficient workflow, defined by a sequence of steps. The conversational module then must be able to navigate autonomously the ontology, moving through the concepts relationships. The selected model is the Petri Net because it lends well for this kind of applications. This model is composed of a set of basic objects: places, transactions and arcs, graphically represented by circles, rectangles and oriented lines. For evaluating the performance of the proposed system an experimental campaign has been developed. An implementation of the Chatbot has been developed and inserted in a Web Site of a tires seller. At the end of the chat session, an email with the suggested model tires has been sent to the potential customer. The email, showed in the store, guaranteeing a 5% discount on tires’ price. In this way, it was possible to check whether the tires suggested by the system were right for the car and the needs of the customer. In two months about five hundreds potential customers (identified with the email address) used the Chatbot and 173 of them showed the email in the store and bought tires. The experimental analysis has been conducted about these 173 customers. First of all the performance of the Chatbot in providing the correct suggestions to the user has been evaluated. In particular, three different situations has been considered: Chatbot furnishes a correct suggestion, Chatbot furnishes a correct suggestion, but it does not fit with the real needs of the customer, Chatbot furnishes a wrong suggestion. The obtained results are the following Chatbot furnished the following results: Correct Suggestion: 113 65,32%, Correct Suggestion, but not suitable for the needs of the customer: 24 13,87%, Wrong Suggestion: 36 20,81%. Analyzing the Wrong Suggestion case, we noticed that the system fails when customer talks about a model that have various versions because it proposes tires of different dimensions. Another critical aspect occurs when the system does not understand what kind of vehicle the customer is considering. In the case of Correct Suggestion, but not suitable for the needs of the customer the main problem is in the identification of the real user needs. From the point of view of the usability a questionnaire about his/her interaction with the Chatbot was submitted to each customer. In general, they find the Chatbot easy to use and user friendly. Comparing it with other Chatbot (for example Telegram Chatbot or similar) customers says that our system is more simple and effective. In this paper, an original approach to a Chatbot has been introduced. In particular, the proposed system is based on the Petri Net formalism. A real case has been investigated developing a Chatbot, for a tires’ seller. The results obtained by the experimental campaign are satisfying and show the good perspective of this kind of approach. Further developments involve the application of the proposed approach in various contexts and an improvement of the recommender approach.

Context-aware computing for improving the touristic experience: A pervasive app for the Amalfi coast

In the touristic field, the trip is defined as the set of goods and services used by the traveler; Is organized by a manufacturer (tour operator) who designs and builds a reference path consistent with customer demand. Designing an itinerary is, therefore, a complex task because many variables need to be considered. It should be emphasized that each route has to change depending on the users characteristics and needs. In this paper, we introduce a Context Aware approach that can gather content and services in a context and present them according to user typology. The whole system is adaptive by being able to record context changes through the paradigm of the internet of things. A case study applied to the Amalfi Coast in Southern Italy was conducted as an experimental campaign.