Adaptive Complex Data-Intensive Web Systems via Object-oriented

Paradigms: A Real-life Case Study

Alfredo Cuzzocrea

1,2 a,*

and Edoardo Fadda

3,4 b

iDEA Lab, University of Calabria, Rende, Italy

LORIA, Nancy, France

DAUIN Department, Politecnico di Torino, Torino, Italy

ISIRES, Torino, Italy

Keywords: Adaptive Complex Data-Intensive Web Systems, Object-oriented Adaptive Complex Data-Intensive Web

Systems, Real-life Case Studies.

Abstract: This paper focuses the attention on the emerging class of Adaptive Complex Data-Intensive Web Systems

(ACDIWS), which start from classical Adaptive Web Systems (AWS) and add innovative characteristics of

complex application scenarios and big Web data. One among the state-of-the-art results is represented by the

OO-XAHM framework, which makes use of an object-oriented approach for achieving the adaptation effect

over complex data-intensive Web systems. Along this fortunate line of research, this paper contributes to the

research context with a real-life case study that shows the potentialities of OO-XAHM on the Web portal of

the well-known Italian archaeological site Pompeii.

1 INTRODUCTION

In the era of Internet, attention of the last decades was

on personalized services and it is going to be again

the same for the future decades. Users access services

based on their “attention” and Web sites provide

services accordingly. Platforms such as social

networks (Facebook, Twitter, Instagram, etc.), online

video-sharing platforms (Youtube, Netflix, etc.)

online shopping (Amazon, Ebay, etc.) and many

others, aim at keeping the user as much time as

possible on their Web sites. In such a way, they are

able to collect more data and to present to more

personalized contents. In orde to have user willing to

spent time on a Web site, the content must be

appreciated by the user.

In order to achieve such a goal two enabling

technologies are needed: Data Mining Techniques

(e.g., (Olson & Delen, 2008)) and Adaptive Web

Systems (e.g., (Brusilovsky et al., 1998; Brusilovsky

& Maybury, 2002)). The former techniques are

https://orcid.org/0000-0002-7104-6415

https://orcid.org/0000-0002-5599-6349

*This research has been made in the context of the

Excellence Chair in Computer Engineering – Big Data

Management and Analytics at LORIA, Nancy, France”

important due to the need to exctract useful

information from the huge amount of data collected.

Despite this, it is common knowledge that, nowadays,

while Data Mining, also combined with emerging Big

Data Technologies (e.g., (Furht & Villanustre, 2016;

Akash et al., 2017; Cuzzocrea et al., 2015, Cuzzocrea

et al., 2014)), has provided the instrument for

implementing in practice a vast range of data analysis

tools, designing intelligent techniques for Web

personalization (e.g., (Brusilovsky, 2003)) is still a

real, effective research challenge (e.g., (Hariyanto &

Köhler, 2020; Elmabaredy et al., 2020). Its need has

further grown in these last years, thus attracting a

plethora of academic and industrial researchers

ranging from the Artificial Intelligence research field

to the Machine Learning and Database Systems ones.

Indeed, adaptive web systems are important

because users are more and more heterogeneous due

to different interests and goals, world-wide

deployment of information and services. Thus,

adapting the Web site content to the user preferences

Cuzzocrea, A. and Fadda, E.

Adaptive Complex Data-Intensive Web Systems via Object-oriented Paradigms: A Real-life Case Study.

DOI: 10.5220/0010481705650572

In Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021) - Volume 2, pages 565-572

ISBN: 978-989-758-509-8

565

is of paramount importance. Moreover, adaptive

systems enable artificial intelligent algorithms to

interact directly with the user (e.g., (Cerone et al.,

2017)). The application fields where content

personalization achieved has proven to be effective

are on-line advertising, direct Web-marketing,

electronic commerce, on-line learning and teaching, etc.

Recently, this paradigm has now been of great

interest thanks to the integration of Web

personalization and big data. The literature now

exposes several contributions on this topics (e.g.,

(Elmabaredy et al., 2020)). As the reader can notice,

the branch of the literature dealing with this topic has

presented several contributios in the recent years, and

the centrality of the topic is re-gaing importance. To

be convinced of this claim, it is sufficient to think of

modern Web-based applications like e-government,

e-procurement, and e-democracy, which promise to

definitively realize the so-called Information Society

that represents one of the most attractive and exciting

challenges for the next years. Morevover, consider a

today case. Due to the ongoing SARS-CoV-2 pandemic,

several high school students cannot attend the physical

lectures, thus creating huge lack in their knowledge.

In this context, having the possibility of learning

thorught a Web platform whose contents adapt to the

student in order to keep his/her as interested as

possible is an application of central importance.

This paper focuses the attention on the emerging

class of Adaptive Complex Data-Intensive Web

Systems (ACDIWS), which start from classical

Adaptive Web Systems (AWS) and adds innovative

characteristics of complex application scenarios and

big Web data (e.g., (Efthymiou et al., 2020)). One

among the state-of-the-art results is represented by

the OO-XAHM framework (Cannataro & Cuzzocrea,

2003), which makes use of an object-oriented

approach for achieving the adaptation effect over

complex data-intensive Web systems. Along this

fortunate line of research, this paper contributes to the

research context with a real-life case study that shows

the potentialities of OO-XAHM on the Web portal of

the well-known Italian archaeological site Pompeii.

We recall the reader that Pompeii was an ancient

city located in the modern city of Pompeii near

Naples, Italy. It was buried under 4 to 6 meters of

volcanic ash and pumice during the eruption of

Mount Vesuvius in 79 aC. Largely preserved under

the ash, the excavated city offered a unique snapshot

of Roman life, frozen at the moment it was buried,

and an extraordinarily detailed insight into the

everyday life of its inhabitants. Due to its unique

characteristics, it is one of the most important Roman

archaeological sites.

From the theoretical point of view, according to

OO-XAHM, an AWS is composed by the following

sets:

 Set of profiles



𝐴 that collects all the

various user profiles:

 Set of web pages Σ𝐴 that contains all the

Web pages of the target Web site;

 Set of information fragments Δ𝐴that

contains all the resources such as videos,

images, etc. that are used in the target Web

site;

 Set of concepts Φ𝐴 that contains the

abstract set of concepts considered in the

target Web site.

In order to link the elements of the set for creating

the web pages, two functions are defined. First one is

the following:

𝛿



𝐴



:Σ



𝐴



→Δ



𝐴



)

that connects the page to the information fragments.

Second one is the following:

𝑘

𝐴

:Σ



𝐴



→Φ

𝐴

 (2

)

that connects the pages to the concepts. Thus, by

properly updating these two functions, it is possible

to dynamically change the content of the target Web

site to meet the user preferences. Several AWS

frameworks using this theoretical framework have

been introduced in the literature. As mentioned, OO-

XAHM, is among the state-of-the-art ones. Despite

the large amount of pubblications describing the

approaches and their property, there no paper related

to applications of the framework to real case studies.

This justifies the present paper, where we present an

application of the OO-XAHM framework to the

Pompeii Web portal (Pompeii Sites, 2020). In fact, it

should be note that, every day, a huge amount of

people visits the city of Pompeii. Each one of them

has different knowledge, goals and interests. The

Pompeii Web portal offers a huge amounts of

information, and therefore the OO-XAHM

framework is particularly suitable for the needs of

gain effective and efficient Web content

personalization.

2 RELATED WORK

As mentioned in Section 1, recently there has been a

new interest in the context of adaptive web systems,

combined with emerging contexts like big data. Here,

we review some relevant approaches.

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Figure 1: UML Class Diagram for the Pompeii Web Portal.

(Hariyanto & Köhler, 2020) proposes a Web-

based adaptive e-learning application for

engineering students, and its experimental

evaluation. The primary purpose of this study is to

evaluate the Web-based adaptive e-learning

application based on the expert-based assessment.

There are two aspects of assessment considered in

this study, the first one evaluates the e-learning

system in terms of the learning content and its

structure, and the second one focuses on the media

aspect. The process of evaluation is conducted by

developing the instruments of evaluation by taking

into account related literature. Then, the content

validity of the instruments is checked by scientific

experts. After that, the assessment is conducted by

two groups of experts in a paper-and-pencil format by

marking one out of four points Likert scale. The result

shows that the adaptive e-learning application is

categorized acceptable to use in the learning process.

(de Vasconcelos et al., 2020) instead focuses on a

methodology for supporting the construction of

adaptive Web applications, called Real-time Usage

Mining (RUM). RUM exploits the rich information

provided by client logs to support the construction of

adaptive Web applications. The main goal of RUM is

to provide useful information about the behaviour of

users that are currently browsing a Web application.

By consuming this information, the application is

able to adapt its user interface in real-time to enhance

the user experience. RUM provides two types of

services as follows: (i) support for the detection of

struggling users; and (ii) user profiling based on the

detection of behaviour patterns.

Finally, (Elmabaredy et al., 2020) presents a study

devoted to assess Web-based adaptive presentation

techniques for enhancing learning outcomes in higher

education. The purpose of this study is to develop and

compare two different techniques of adaptive

presentation techniques (adaptive multimedia/

frames). Moreover, this study aimed at investigating

the effect of both treatments on improving learning

outcomes. The participants are two experimental

groups. One was taught content through the

multimedia-based technique. The other one was

taught content through the frame-based technique.

The results show that the adaptive presentation

techniques have an effect on enhancing students’

learning outcomes. Also, the comparison of the

techniques shows a significant difference between the

mean scores of the two groups in favour of the first

one. The study concludes that the adaptive

multimedia-based technique shows higher impact

relatively than the frame-based technique.

3 OO-XAHM CASE STUDY: THE

POMPEII WEB PORTAL

This Section presents the case study that implement

the proposed technique. The software application

considered is the Pompeii Web portal. The UML

Adaptive Complex Data-Intensive Web Systems via Object-oriented Paradigms: A Real-life Case Study

567

diagram of the underline database is depicted in

Figure 1.

As the reader can notice, the most important table

contains the information of the element Sites (i.e.,

table Site). It contains the name, a picture of the site

and the availability. In fact, it is possible that some

sites are closed due to restoration activities. Each

element Site is linked to one or more address (several

houses have more than one entrance). Element Path

are characterized by a list of Sites, the Length in meter

and the Boolean Handicap that is true if there are the

structure that enable the path to be visited by using a

wheelchair. Furthermore, each site is linked to the

review that the visitors can write. Element Sites can

be on four different types: Wall, Temple, Necropolis

and Gate.

Each one of these tables add important details to

the corresponding site and are linked to the element

Object that can be found in element Site: they are

Painting, Mosaic and Relic. A screen shot of the main

tables are presented in Figure 2, Figure 3, Figure 4,

and Figure 5.

Figure 2: Table Wall.

Figure 3: Table Gate.

In our case study, we focus on three profiles

tourist, researcher and historian. Thus, the set of

profiles



𝐴 is the following:





𝐴







𝑡𝑜𝑢𝑟𝑖𝑠𝑡,𝑟𝑒𝑠𝑒𝑎𝑟𝑐ℎ𝑒𝑟,ℎ𝑖𝑠𝑡𝑜𝑟𝑖𝑎𝑛



)

Each profile 𝑝∈



𝐴 is associated to a final

pages in the set Σ𝐴, defined as follows:



𝐴



𝑡𝑒𝑚𝑝𝑙𝑒𝑠. ℎ𝑡𝑚𝑙,𝑛𝑒𝑐𝑟𝑜𝑝𝑜𝑙𝑖𝑠.ℎ𝑡𝑚𝑙,

𝑔𝑎𝑡𝑒.ℎ𝑡𝑚𝑙

)

Figure 4: Table Necropolis.

Figure 5: Table Temple.

In particular, the profile tourist is associated with

the page temples.html, the profile researcher is

associated with the page necropolis.html and

the profile historian is associated with the page

gate.html. The set of information fragments is the

following:

Δ𝐴



𝑡𝑒𝑚𝑝𝑙𝑒𝐼𝑠𝑖𝑠.𝑗𝑝𝑔, 𝑠𝑎𝑛𝑐𝑡𝑢𝑎𝑟𝑦𝑉𝑒𝑛𝑢𝑠.𝑗𝑝𝑔,

𝑛𝑒𝑐𝑟𝑜𝑝𝑜𝑙𝑖𝑠𝐻𝑒𝑟𝑐𝑢𝑙𝑎𝑛𝑒𝑢𝑚𝐺𝑎𝑡𝑒. 𝑗𝑝𝑔,

𝑛𝑒𝑐𝑟𝑜𝑝𝑜𝑙𝑖𝑠𝑉𝑒𝑠𝑢𝑣𝑖𝑜𝐺𝑎𝑡𝑒.𝑗𝑝𝑔,

𝑛𝑒𝑐𝑟𝑜𝑝𝑜𝑙𝑖𝑠𝑁𝑜𝑐𝑒𝑟𝑎𝐺𝑎𝑡𝑒.𝑗𝑝𝑔,



)

Finally, the set of concepts is the following:



𝐴







𝑟𝑒𝑙𝑖𝑔𝑖𝑜𝑛,𝑎𝑟𝑡,𝑤𝑎𝑟



)

The function 𝛿𝐴 is defined as follows:

𝛿



𝑛𝑒𝑐𝑟𝑜𝑝𝑜𝑙𝑖𝑠.ℎ𝑡𝑚𝑙



𝑛𝑒𝑐𝑟𝑜𝑝𝑜𝑙𝑖𝑠.

𝑗

𝑝𝑔

𝛿



𝑡𝑒𝑚𝑝𝑙𝑒𝑠.ℎ𝑡𝑚𝑙



𝑡𝑒𝑚𝑝𝑙𝑒𝑠.

𝑗

𝑝𝑔

𝛿



𝑔𝑎𝑡𝑒𝑠.ℎ𝑡𝑚𝑙







𝑔𝑎𝑡𝑒𝑠.

𝑗

𝑝𝑔



)

and the function 𝑘𝐴 is defined as follows:

𝑘



𝑛𝑒𝑐𝑟𝑜𝑝𝑜𝑙𝑖𝑠.ℎ𝑡𝑚𝑙



𝑛𝑒𝑐𝑟𝑜𝑝𝑜𝑙𝑖𝑠

𝑘𝑡𝑒𝑚𝑝𝑙𝑒𝑠.ℎ𝑡𝑚𝑙𝑟𝑒𝑙𝑖𝑔𝑖𝑜𝑛

𝑘



𝑔𝑎𝑡𝑒𝑠.ℎ𝑡𝑚𝑙







ℎ𝑖𝑠𝑡𝑜𝑟𝑖𝑎𝑛



)

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Figure 6: Main Path Proposed for the Profile tourist.

Figure 7: Information Fragments Proposed for the Profile tourist.

The path proposed for the profile tourist covers

the most important temples. In particular, the temples

that can be visited are the one Isis, the one of Venus,

the one of Athena, the one of Hercules and some

small temples inside the major house of the city. We

show in Figure 6 and Figure 7 an example of tour for

the profile tourist plus the related information

fragments. The tour considers the three most

important temples (i.e., Isis, Venus, Athena and

Hercules), their visit presenting a complete

description of the art and the religion in the Pompeii

world. In the path, other temples are not presented

because of the time constraints for the visit. By

clicking on the red square marker, the user have

access to a page describing the site. In Figure 7, we

show, in particular, the page of the description of the

temple of Isis.

The path proposed for the profile researcher,

shown in Figure 8, passes near the main necropolis of

the city, i.e. the necropolis of the Herculaneum gate,

the one of the Nocera gate and the one of the Vesuvio

gate.

Adaptive Complex Data-Intensive Web Systems via Object-oriented Paradigms: A Real-life Case Study

569

Figure 8: Main Path Proposed for the Profile researcher.

Figure 9: Information Fragments Proposed for the Profile researcher.

Despite the fact that other necropolises exist, the

application does not suggest them because they are

less important and belong to period before the Roman

empire, thus they are not important for the profile

considered. As in the other pages, by clicking on the

red pins on the map, the page shown in Figure 9

appears. It shows the main information of the three

necropolises proposed in the path. The page does not

contain graphical information fragments because the

sites have a huge geographic extension, thus a single

information fragment is not enough to present the

sites.

Finally, for the profile historian, the path

proposed by the application is shown in Figure 10,

while the Figure 11 shows the associate information

fragments. The path passes near the three of the four

most important gates of the city, i.e. the Herculaneum

gate, the Marina gate and the Nocera gate. The user

considered for this profile needs to travel by

wheelchair, thus, the path presented in Figure 11 can

be travel in that way. This is the main reason of the

path passing outside the city. In fact, the old roman

streets have small sidewalk often rugged, thus travel

by wheelchair becomes very difficult. Furthermore,

in the street, there are often rocks bulging that were

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Figure 10: Main Path Proposed for the Profile historian.

Figure 11: Information Fragments Proposed for the Profile historian.

for the pedestrian crossing of the street. These

increase the difficulty to move inside the city by

wheelchair. The management of the historical site of

Pompeii is looking for a solution. In fact, in several

part of the city, they added boardwalk; nevertheless,

the work is not completed for the trips outside the

most important house of the city. Due to the

aforementioned problem, the fourth gate (the Vesuvio

gate) is not in the considered in the path since it is not

reachable by wheelchair. As in the previous pages, by

clicking on the pins some details of the gates are

shown in another page (see Figure 11). The page of

details shows also images of the three gates; this is

because just one information fragment well

represents what the user is going to see.

4 CONCLUSIONS

Within the complex context of AWS, this paper has

complemented the main research contributions

carried out by the state-of-the-art OO-XAHM

proposal (Cannataro & Cuzzocrea, 2003). We

presented a complete case study following the

attention on the Web portal of the well-known Italian

Adaptive Complex Data-Intensive Web Systems via Object-oriented Paradigms: A Real-life Case Study

571

archaeological site Pompeii. Our study has clearly

demonstrated how OO-XAHM is capable of adapting

the Web content to three different profiles, namely:

tourist, researcher and historian. We firmly believe

that adaptation paradigms will become more and

more important in the emerging context of big Web

data. This paper could thus represent an important

milestone to this end. In future work, we plan to

consider other innovative aspects of adaptive

paradigms (e.g., (Kim, 2021; Bhattacharjee & Mitra,

2021; Mohammad et al., 2021)) and big data research

(e.g., (Fisichella et al., 2011; Bellatreche et al., 2010;

Braun et al., 2017; Cuzzocrea et al., 2012)).

ACKNOWLEDGEMENTS

This research has been partially supported by the

French PIA project “Lorraine Université

d’Excellence”, reference ANR-15-IDEX-04-LUE.

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