A Context Aware Approach for Promoting Tourism Events: The Case

of Artist’s Lights in Salerno

Francesco Colace

, Saverio Lemma

, Marco Lombardi

and Francesco Pascale

DIIn, University of Salerno, Via Giovanni Paolo II, 132, 84084, Fisciano, Salerno, Italy

SIMASLab, University of Salerno, Via Giovanni Paolo II, 132, 84084, Fisciano, Salerno, Italy

Keywords: E-Citizenship, Context-aware Computing, Adaptive Systems.

Abstract: 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

results.

INTRODUCTION

The adoption of Future Internet (FI) technology and of

its most challenging components like the Internet of

Things (IoT) and the Internet of Services (IoS), can

constitute the basic building blocks to progress

towards a unified ICT platform for a variety of

applications within the large framework of smart cities

projects (Atzori et al., 2001; Colace et al., 2015c). In

addition, recent issues on participatory sensing, where

every day mobile devices like cellular phones form

interactive, participatory sensor networks enabling

public and professional users to gather, analyze and

share local knowledge (Hernandez-Munoz et al.,

2011; Colace et al., 2005), seem to fit the smartness

requirements of a city in which also people have to

play an active role. Eventually, the cloud computing

technologies provides a natural infrastructure to

support smart services (Colace et al., 2015a).

One of the fields that can take great advantages

from such technologies is tourism (Schaffers et al.,

2011). In this scenario, persons (citizens, tourists, etc.)

and objects (cars, buildings, rooms, sculptures, etc.)

equipped with appropriate devices (GPS, smart-

phone, video cameras, temperature/humidity sensors,

etc.) constitute a particular social network in which all

the mentioned entities can communicate (Komninos et

al., 2011).

Exchanged and produced data can be exploited by

a set of applications in order to make the system

“smart”. From a more general point of view, the social

network can be seen as composed of a set of Single

Smart Spaces (S3) (indoor museums, archaeological

sites, old town centers, etc.), each needing particular

ICT infrastructure and service that transforms the

physical spaces into useful smart environments. Here,

one of the most challenging and interesting research

problem is to model context awareness in a S3 and

design context aware applications able to provide

useful data and services depending on the current

context occurrences (Colace et al., 2015b; Colace et

al., 2014).

Context is not just a simple profile that describes

the surroundings of data. Rather, context is better

described as any piece of information that can be used

to characterize the situation of an entity such as a

person, a place, or any other relevant object/aspect in

the interaction between a user and an application. In

this paper, we try to give an answer to the problem of

the context representation using the Context

Dimension Tree formalism (Bolchini et al., 2006a;

Bolchini et al., 2009).

On the basis of what has been previously

described, this work will be organized in this way: in

the following paragraph, we will describe the concept

of context and how it can be declined in a modern way

thanks to the use of new technologies. Then, we will

introduce a context-based approach able to give, inside

752

Colace, F., Lemma, S., Lombardi, M. and Pascale, F.

A Context Aware Approach for Promoting Tourism Events: The Case of Artist’s Lights in Salerno.

DOI: 10.5220/0006370007520759

In Proceedings of the 19th International Conference on Enterprise Information Systems (ICEIS 2017) - Volume 2, pages 752-759

ISBN: 978-989-758-248-6

a Christmas event in a little town, services and

contents useful for the user. Some experimental results

will be presented in the last part of the paper.

MOTIVATING EXAMPLE

In this section, we describe a typical application in the

tourist domain in order to better understand the main

features of the proposed system. In particular, we

consider a tourist that during her/his vacation in

Campania desires to see Artist’s Lights Christmas

event in Salerno, a beautiful town located in the South

of Italy.

Some of the features of context-aware systems are

given below:

 contextual sensing: ability to sense context

information and present it to the user;

 contextual adaptation: ability to execute or modify

a service automatically at runtime based on the

context;

 context resource discovery: ability to discover and

use resources and services related to the current

context;

 contextual augmentation: ability to supplement

digital data with the user’s context.

In particular, to be considered smart, the

environment related to the Artist’s Lights event should

provide a set of smart services for:

 suggesting the visit of the most important

Christmas lights;

 having information about the Christmas lights in

Salerno;

 accessing to proper multimedia guides describing

the Christmas lights that are in Salerno;

 recommending special visit paths (Il Mito, Il

Sogno, Il Tempo, Il Natale);

 monitoring the weather condition;

 showing the timetable of the transport services

located in Salerno;

 saving the visit in a multimedia album and sharing

it with friends.

For improving their effectiveness, these services

and contents have to be furnished to the user in the

right context and at the right timing. Therefore, it is

important the context awareness of the framework and

the opportunity to use it by mobile devices (Colace et

al., 2015d). Another important feature of the system is

the ability to suggest resources that usually are not

considered as mainstream.

In order to give the most suitable contents to the

users, in this paper we introduce a context aware

system able to tailor data and services depending on

the context and the users’ needs.

Data about resources and services are collected from a

knowledge base built by a group of experts and

collecting information from the various social

networks.

In the next paragraphs, more details about context

awareness and the application of the proposed

approach in real context will be furnished.

CONTEXT AWARENESS

The term context has been defined by many

researchers. One of the most cited definitions of

context is the definition of Dey et al. (1999) that defines

context as “any information that can be used to

characterize the situation of an entity. An entity is a

person, place, or object that is considered relevant to

the interaction between a user and an application,

including the user and applications themselves.”

We accept the definition of context provided by

Dey et al. to be used in this research work, because this

definition can be used to identify context from data in

general.

The originators of the term context awareness are

Schilit and Theimer who in 1994 introduced and

defined Context-aware computing as “the ability of a

mobile user's applications to discover and react to

changes in the environment they are situated in”

(Schilit et al., 1994).

Pascoe et al. (2000) describe context awareness as

the ability of the computing devices to detect, sense,

interpret and respond to aspects of a user’s local

environment and the computing devices them selves.

Dey and Abowd have refined these definitions into

a more general definition what a context-aware system

is. In this definition they use context in the definition

of a context-aware system. Since context has already

been defined and classified in the above it is logical to

use these elements in the definition of context

awareness: “A system is context-aware if it uses

context to provide relevant information and/or services

to the user, where relevancy depends on the user's

task”.

If we wanted to classify the context awareness

categories, we could consider that presented in

Bisgaard et al. (2004):

1. Presentation of information and services to a user,

is the systems ability to select appropriate

information and services according to the current

context and make these available to the user at the

correct time.

2. Automatic execution of a service, is when the

system automatically performs actions and updates

A Context Aware Approach for Promoting Tourism Events: The Case of Artist’s Lights in Salerno

753

the system according to events in the context.

3. Tagging of context to information for later

retrieval, is applying information to the context so

that the information may the retrieved later when

the user enters the same context again.

Context-aware systems are changing over the years

since its introduction, several existing context-aware

systems were reviewed.

Based on the characteristics, existing context-

aware systems are broadly classified into four

categories, namely the first generation, second

generation, third generation and fourth generation of

context-aware systems (Meena et al., 2014).

Examples of first generation context-aware systems

are tour guide, shopping assistant, phone call

forwarding and location information providing.

The main focus during this generation is acquisition

of location from the sources. This systems are named

location based service systems.

The second generation context-aware systems

initiated focusing on achieving more number of

context-aware applications starting from homogenous

devices to heterogenous devices.

Third generation of context-aware systems begins

to focus on context knowledge sharing among the

network. It concentrates on markup languages, for

example Web Ontology Language (OWL).

Fourth generation of context-aware systems are

working in ambient environment.

What are the mobile context-aware applications

for?

In this section we will describe some systems and

ideas behind the applications.

One of the very first attempts to make a context-

aware system is the CyberGuide (Abowd et al., 1997)

which was created back in 1996. The CyberGuide was

intended to work as a citywide guide system which

could lead people to the sites which they wished to see

and also provide a local mobile guide inside the

different attractions around the city. Once inside a

museum or a similar site the CyberGuide functions as

a personal tour guide which leads the user around the

exhibit and based on knowledge of the user’s location

provides information about the pieces of art in the

vicinity.

SenSay (Siewiorek et al., 2003) is one example of

a context-aware system that attempts to adapt to

dynamically-changing environmental and

physiological states. The system relies on a sensor

network that utilises a person’s mobile phone as a

primary source of context information, although the

use of applications (e.g. calendars, task lists) and body-

embedded sensors was also targeted.

AnonySense (Shin et al., 2010), a privacy-aware

architecture for collaborative pervasive applications

that use mobile sensing. Mobile sensor data is

anonymized before its use by any of the applications.

SOCAM (Gu et al., 2004) is a service oriented

ontology based context-aware middleware. It supports

semantic representation and reasoning of context. It

also divides context into upper and lower level

ontologies such as interpreted context through physical

world, and memory and battery status respectively. It

allows adaptability by listening, detecting and

invocating events for application services.

GeoNotes by Espinoza et al. is a system for

abstracting location information for location-aware

applications (Espinoza et al., 2001). The system

architecture is constructed to support shared

information for mobile devices, exactly to leave notes

atspecific places for other users to be read. A user

creates notes and sticks it to certain places, where other

users can read them. Notes can be targeted at a single

user or a whole user group. Vice versa a specific user

can create and apply filters to perceive only a subset of

the notes associated to a certain place.

In the following paragraph, we will present an

approach to the management of the context and the

contextualization of its associated contents and

services.

CONTENTS AND SERVICES

CONTEXTUALIZATION

In order to make contextualized queries, it is necessary

to define a model for the representation and

management of the context itself, which allows

filtering the resources obtained, on the basis of

contextual parameters (user position, user profile, user

friends, etc.): this operations are made through the

Context Dimension Tree (CDT) (Tanca et al., 2006).

Therefore, the result shows itself like a well-

organized information that presents a general

introduction about the place reached by the user,

according to his/her interests and enriched with the

experiences shared by similar users, and a list of the

main suggested attractions about the near places

visited by the friends.

In particular, CDT is used to be able to represent,

in a graphic form, all possible contexts that you may

have within an application. CDT plays a fundamental

role in tailoring the information space according to the

user’s information needs, as well as an analysis of

relevant features of context models. It is thus

important to notice that this notion of context is strictly

connected to the considered application and is not

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754

meant to model the general knowledge concerning one

or more areas of interest, a situation where a data

schema, or a domain-ontology may be better suited

(Bolchini et al., 2006b; Colace et al., 2015e).

CDT is a tree composed of a triad <r; N; A> where

r indicates its root, N is the set of nodes of which it is

made of and A is the set of arcs joining these nodes.

A dimension node, which is graphically

represented by the color black, is a node that describes

a possible dimension of the application domain; a

concept node, on the other hand, is depicted by the

color white and represents one of the possible values

that a dimension may assume. Each node is identified

through its type and a label.

The children of the root node r are all dimension

nodes, they are called top dimension and for each of

them there may be a sub-tree. Leaf nodes, instead,

must be concept nodes. A dimension node can have,

as children, only concept nodes and, similarly, a

concept node can have, as children, only dimension

nodes. In addition to nodes, you can use other

elements: the parameters, which may arise both from

a dimension node (graphically represented by a white

square) and from a concept node (white triangle),

submitting them to particular constraints. In fact, a

concept node can have more than one parameter, while

a dimension node can have only a parameter and only

in case it has not already children nodes. The

introduction of parameters is due to their usefulness in

shaping the characteristics that can have an infinite or

very high number of attributes. For example, a node

representing Cost dimension risks having a high

number of values that should be specified by as many

concept children nodes. In a similar case, it is therefore

preferred to use only one parameter, whose value will

be specified in each case. Leaf nodes, in addition to

concept nodes, can also be parameters. In general,

each node has a parameter corresponding to a domain,

dom(nP). For parameter nodes connected to concept

nodes, the domain can be a set of key values from a

relational database, while in case of parameter nodes

connected to dimension nodes, the domain is a set of

possible concept nodes of dimension.

Therefore, CDT is used to systematically describe

the user needs, and to capture the context the user is

acting in. It plays a fundamental role in tailoring the

target application data according to the user

information needs. Once the possible contexts have

been designed, each must be connected with the

corresponding view definition. In this ways, when the

context becomes current, the view is computed and

delivered to the user (Parent et al., 2007).

In fact, through the CDT, it is possible, after

analyzing the domain of application, to express the

size characteristics and values they can take in a

graphical way by, respectively, dimension nodes and

concept nodes or parameters.

The assignment to a dimension of one of its

possible values is a context element. The context

element can be considered the main feature of the

application, by which a context can be decomposed.

The moment you make the formulation of the context,

you must specify all the context elements that are part

of it and that enable its creation. Any context is

expressible by an “and” combination of the context

elements to which they are peculiar.

By definition, you can begin to understand how

you will create views based on data relating to each

context; in fact, they will be built starting from the

portions of the database and then from the partial

views, associated to the context element that takes part

into context information.

The CDT elaboration is composed of

methodologies and phases to obtain contextual

resources. The methodology has been realized in order

to manage the database and to carry out reductions of

their content based on the context. The purpose is to

help the designer in the definition of all contexts

relevant to the considered application and, later, in the

association to each context of the portion of the

database containing the relevant data about the

context.

The methodology consists of three main phases,

which we will see in detail later: design phase of the

CDT, definition phase of partial views and

composition phase of global views (Annunziata et al.,

2016).

1. Design phase of the Context Tree: in this phase, the

CDT is designed to identify significant context

elements for the considered application. In fact, it

focuses on the definition of contexts and on the

elements that compose them. These contexts must

be identified and shaped, indicating particular

elements that characterize each of them. As it has

been said, it is available a special tool called CDT

to make context design. Various CDT were made

for specific environments in order to represent and

manage a multitude of different contexts and in

order to identify, represent, preserve and make

available cultural points for each type of user.

2. Definition phase of partial views: after the

definition of all the contexts and their context

elements, in this step a different portion of the

database is associated to each context element,

containing the relevant data for it. In practice, the

goal is to find the appropriate value for a given

dimension, in order to obtain, by means of the

A Context Aware Approach for Promoting Tourism Events: The Case of Artist’s Lights in Salerno

755

values of all the dimensions, a valid query and

specific to the context in which the user is located.

3. Composition phase of global views: this is the

phase where you have the automatic generation of

views associated with each context, which is made

starting from partial views associated with context

elements. After the creation of the global views of

the contexts, the answers to questions that will be

asked to the system will be developed from these

views and, in particular, from the view associated

with the context in which you are located when the

query is performed.

In particular, once defined the values for each

dimension, you can use all the information obtained in

order to identify the right context and offer contextual

resources for the user.

In figure 1, it is shown a general designed CDT,

called Meta CDT, which is the starting point for the

design of a specific CDT that can be exploited in

contextual applications (Colace et al., 2015d).

You may note six top dimensions, which

correspond to the questions of the 5W1H method:

Location (WHERE), Role (WHO), Time (WHEN),

Situation (HOW), Interest (WHAT) and Utilization

(WHY).

In particular, there are two types of users and

eleven categories of interests. In this case, as shown in

figure 2, a partial view could be related to dimension

“Role”: once logged in, the application is able to

recognize the user and to know more precisely

whether he/she is, for example in tourist areas, a

resident or a tourist. Thus, the value “tourist” of

dimension “Role” is a partial view for the current

context: using this knowledge, you can exclude certain

resources, not suitable or useful to the tourist role.

A context element is defined as an assignment

d_name

= value, where d_name

indicates a possible

size or undersize of CDT (it is the label of a dimension

node), while value may represent the label of one of

the concept nodes that are children of the considered

dimension node or the value of a parameter referring

to one of these concept nodes or the value of a

parameter referring to the considered dimension node.

For example, these assignments are possible

context elements:

Interest = “tourism”, Location = $locationID (for

example, ID = 3), Role = $userID->role (for example,

ID = 15), Utilization = “holiday”. A context is

specified as: ˄(d_name

= value): it is defined as an

“and” among different context elements.

Several context elements, combined with each

other by means of an “and”, damage, therefore, the

origin of a context (Casillo et al., 2016a).

For example, a possible framework that can be

obtained from the previously seen CDT, through the

context elements that we have listed, is:

Figure 1: Meta Context Dimension Tree.

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C = (Location = $locationID (ID=3)) ˄ (Role=

$userID->role (ID=15)) ˄ (Time = “now”)

˄ (Situation = “routine”) ˄ (Interest = “tourism”) ˄

(Utilization = “holiday”)

The context is defined as a user, interested in tourism,

who uses the contextual app on vacation, in a called

place.

Figure 2: Example of Partial Views.

A CONTEXT AWARE APP FOR

CHRISTMAS TOURISTS

In this section, we will present Smart Artist’s Lights,

contextual app designed and implemented

according

to what was described previously. In

particular, we

have thought to apply the approach in

the context of

Artist’s Lights Christmas event, that every year is held

in Salerno (Regione Campania in Italy) and that

involves hundreds of thousands of tourists.

From November to January, with light installations,

some by local artists exclusively for Salerno, scattered

through the main streets and in the most beautiful and

attractive corners of the city center.

In this phase, we

have collected the services and

contents potentially

useful for the citizens and situate

them on the map

defining the activation zones (figure

3).

Figure 3: Definition of the activation areas of services and

contents.

Moreover, we have defined the different typologies of

citizens (tourist and expert user) associating

them to

a previously established set of services and

contents.

Having the town a series of Christmas contents,

have developed services and contents in support

them too.

All information about places of worship and

shops

has been uploaded, for any building or area of

potential.

The App has been developed with hybrid

technologies (Ionic Framework and Apache Cordova)

to allow an

easier publication both in Android and

Apple

environment (figure 4 and figure 5).

Figure 4: Screenshots with some features of contextual

application.

Figure 5: Screenshots with other features of contextual

application.

The experimental phase aims to evaluate the proposed

contextual model. Initially, the App has been

presented to the population in

November 2016. They

have been involved overall about 1000 tourists

between 18 and 60 years old. During this event, the

app has been installed on the mobile devices of the

tourists.

After having interacted for some days with the

application, the participants have then answered on the

basis of the Likert scale to fourteen statements,

divided into four sections. To every question present

in the section, five possible answers have been

associated: I strongly agree – I agree – Undecided

(Neither agree nor disagree) – I disagree- I strongly

disagree.

The questionnaire in detail is the following:

Section A: App – Context

• A1. The App gives the user tailor-made contents

A Context Aware Approach for Promoting Tourism Events: The Case of Artist’s Lights in Salerno

757

and services in the right place.

• A2. The App allows the user to know several item

of the Artist’s Lights.

• A3. The App supplies services according to the

interests selected in the user profile.

Section B: App Lights – Further aspects

• B1. Information about each item of Artist’s Lights

is very useful.

• B2. The contents, such as descriptions and images,

are of high quality and represent one of the strong

points of Artist’s Lights.

• B3. The services associated to the items allow a

higher immediacy than a classic research on the

Internet.

Section C: App – Functionality

• C1. The plan itinerary service allows easily

realizing an itinerary in the Artist’s Lights

according to the user’s preferences.

• C2. The explore surroundings service is very

useful to know what there is nearby and eventually

reach them.

• C3. The functionality of QR code in inner

environments can be well used.

Section D: App – Future developments

• D1. It would be interesting to have a higher

integration with the main social networks.

• D2. It would be interesting to insert the available

time in the plan itinerary service.

Table 1 presents a synthesis of the answers of the

participants to each declaration.

Table 1: Experimental results.

Likert

Scale

Strongly

agree

Agree

Neither

agree

nor

disagree

Disagree

Strongly

disagree

303 580 92 15 10

487 422 55 20 16

418 512 55 9 6

315 562 70 35 18

294 502 132 42 30

440 514 27 11 8

596 366 24 6 8

387 493 79 24 17

331 519 95 33 22

458 478 27 19 18

367 435 117 47 34

As shown in this table, of the 1000 participants who

have interacted with the application, many agree

and/or strongly agree that the system gives appropriate

contextual information about the place, further aspects

and functionality are very useful and future

developments are interesting. Instead, only in few

cases, the participants do not are particularly satisfied.

As can noticed from the figure 6, users show

great

appreciation for the app. In general, they

appreciated

the proposed contents and services.

Figure 6: Graphic analysis of experimental results.

CONCLUSIONS

This paper proposes the use of a Context-Aware

Approach for the selection of the most suitable

services and contents for a user in a certain context.

The system is based on the concept of Context

Dimension Tree, a graphical formalism able to model

a context by the approach of the 5W1H method.

The propose approach has been implemented in an

App that furnishes services personalized for the needs

of the user according to the context where he/she is.

The App bases its ‘contextual’ functioning on the

adoption of the CDT that is able to shape the context

and the actions to implement.

It has been

developed for the Artist’s Lights

Christmas event and the

results have been satisfying.

The following

activities have as purpose the

application of the

proposed methodology to more

complex

environments, for dimension and number of

potential

places to manage.

ACKNOWLEDGEMENTS

The research reported in this paper has

been

supported by the Project Cultural Heritage

Information System (CHIS) PON03PE_00099_1

CUP E66J140000 70007 – D46J1400000 0007 and

the Databenc District.

REFERENCES

Abowd, G. D., Atkenson, C. G., Hong, J., Long, S., Kooper,

R., Pinkerton, M., 1997. Cyberguide: A mobile context-

aware tour guide. Wireless Networks, vol. 3, pp. 421-

433.

ICEIS 2017 - 19th International Conference on Enterprise Information Systems

758

Annunziata, G., Colace, F., De Santo, M., Lemma, S.,

Lombardi, M., 2016. ApPoggiomarino: A Context

Aware App for e-Citizenship. The 18th International

Conference on Enterprise Information Systems (ICEIS).

Atzori, L., Iera, A., Morabito, G., 2010. The internet of

things: A survey. Computer Networks, 54(15), pp. 2787–

2805.

Bolchini, C., Curino, C., Schreiber, F.A., Tanca, L., 2006a.

Context integration for mobile data tailoring. SEBD

2006, pp. 48-55.

Bolchini, C., Curino, C., Quintarelli, E., Schreiber, F.A.,

Tanca, L., 2006b. A survey of context models and a

preliminary methodology for context driven data view

deﬁnition. Technical Report 4.1, ESTEEM Project.

Bolchini, C., Curino, C., Quintarelli, E., Schreiber, F.A.,

Tanca, L., 2009. Context information for knowledge

reshaping. Int. J. Web Eng. Technol. 5(1), pp. 88-103.

Bisgaard, J. J., Heise, M., Steffenses, C., 2004. How is

Context and Context-awareness Defined and Applied? A

Survey of Context-awareness. Aalborg University.

Casillo, M., Cerullo, L., Colace, F., Lemma, S., Lombardi,

M., Pietrosanto, A., 2016a. An Adaptive Context Aware

App for the Tourism. In Proceedings of the The 3rd

Multidisciplinary International Social Networks

Conference on SocialInformatics 2016, Data Science

2016 (p. 26). ACM.

Casillo, M., Colace, F., Lemma, S., Lombardi, M.,

Pietrosanto, A., 2016b. An Ontological Approach to

Digital Storytelling. In Proceedings of the The 3rd

Multidisciplinary International Social Networks

Conference on SocialInformatics 2016, Data Science

2016 (p. 27). ACM.

Colace, F., Foggia, P., Percannella, G., 2005. A probabilistic

framework for TV-news stories detection and

classification. IEEE International Conference on

Multimedia and Expo, ICME 2005, art. no. 1521680, pp.

1350-1353.

Colace, F., De Santo, M., Greco, L., 2014. An adaptive

product configurator based on slow intelligence

approach. International Journal of Metadata, Semantic

and Ontologies (IJMSO), Vol.9, No.2, pp. 128-137.

Colace, F., Greco, L., Lemma, S., Lombardi, M., Yung, D.,

Chang, S.K., 2015a. An Adaptive Contextual

Recommender System: a Slow Intelligence

Perspective. The Twenty-Seventh International

Conference on Software Engineering and Knowledge

Engineering (SEKE), pp. 64-71.

Colace, F., De Santo, M., Greco, L., Moscato, V., Picariello,

A., 2015b. A collaborative user-centered framework for

recommending items in Online Social Networks.

Computers in Human Behavior 51: pp. 694-704.

Colace, F., De Santo, M., Lemma, S., Lombardi, M., Rossi,

A., Santoriello, A., Terribile, A., Vigorito, M., 2015c.

How to Describe Cultural Heritage Resources in the Web

2.0 Era? Proceedings - 11th International Conference on

Signal-Image Technology and Internet-Based Systems,

SITIS 2015, art. no. 7400656, pp. 809-815.

Colace, F., Greco, L., Lemma, S., Lombardi, M., Amato, F.,

Moscato, V., Picariello, A., 2015d. Contextual Aware

Computing and Tourism: A Case Study. The Eleventh

International Conference on Signal-Image Technology &

Internet-Based Systems (SITIS), pp. 804-808.

Colace, F., De Santo, M., Greco, L., Napoletano, P., 2015e.

Weighted Word Pairs for query expansion, Information

Processing and Management, 51 (1), pp. 179-193.

Dey, A. K., Abowd, G. D., 1999. Towards a Better

Understanding of Context and Context-Awareness.

Proceedings of the 1st international symposium on

Handheld and Ubiquitous Computing, pp. 304-307.

Espinoza, F., Persson, P., Sandin, A., Nyström, H.,

Cacciatore, E., Bylund, M., 2001. GeoNotes: Social and

Navigational Aspects of Location-Based Information

Systems, International Conference on Ubiquitous

Computing, pp. 2-17.

Gu, T., Pung, H. K., Zhang, D.Q., 2005. A service oriented

middleware for building context aware services. J. Netw.

Comput. Appl., vol. 28, no. 1, pp. 1–18.

Hernandez-Munoz, J. M., Vercher, J. B., Munoz, L.,

Galache J. A., Presser, M., Hernandez Gomez, L. A.,

Pettersson, J., 2011. Smart cities at the forefront of the

future internet. Future Internet Assembly, LNCS, 6656,

pp. 447–462.

Komninos, N., Schaffers, H., Pallot, M., 2011. Developing

a policy roadmap for smart cities and the future internet.

In eChallenges e-2011 Conference Proceedings, pp.

286-306.

Meena, K., Sivakumar, R., 2014, Human-computer

interaction.

Parent, C., Schewe, K., Storey, V., Thalheim, B., 2007.

Conceptual Modeling - ER 2007, 26th International

Conference on Conceptual Modeling.

Pascoe, J., Ryan, N., Morse, D., 2000. Using while moving:

HCI issues in fieldwork. ACM Transactions on

Computer-Human Interaction (TOCHI), vol. 7, pp 417-

437.

Schaffers, H., Komninos, N., Pallot, M., Trousse, B.,

Nilsson, M., Oliveira, A., 2011. Smart cities and the

future internet: Towards cooperation frameworks for

open innovation. The Future Internet, pp. 431–446.

Schilit B., Theimer M., 1994. Disseminating Active Map.

Information to mobile Hosts. IEEE Network, vol. 8, pp

22-32.

Shin, M., Cornelius, C., Peebles, D., Kapadia, A., Kotz, D.,

Triandopoulos, N., 2010. AnonySense: A system for

anonymous opportunistic sensing. Journal of Pervasive

and Mobile Computing.

Siewiorek, D., Smailagic, A., Furukawa, J., Krause, A.,

Moraveji, N., Reiger, K., Shaffer, J., Wong, F.L., 2003.

Sensay: A context-aware mobile phone. In Proceedings

of the 7th IEEE International Symposium on Wearable

Computers, ISWC ’03, Washington, DC, USA.

Tanca, L., Bolchini, C., Curino, C., Schreiber, F.A., 2006.

Context integration for mobile data tailoring. Italian

Symposium on Database Systems (SEBD), pp. 48-55.

A Context Aware Approach for Promoting Tourism Events: The Case of Artist’s Lights in Salerno

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