Personalization in cultural heritage: the road travelled and the one ahead

Over the last 20 years, cultural heritage has been a favored domain for personalization research. For years, researchers have experimented with the cutting edge technology of the day; now, with the convergence of internet and wireless technology, and the increasing adoption of the Web as a platform for the publication of information, the visitor is able to exploit cultural heritage material before, during and after the visit, having different goals and requirements in each phase. However, cultural heritage sites have a huge amount of information to present, which must be filtered and personalized in order to enable the individual user to easily access it. Personalization of cultural heritage information requires a system that is able to model the user (e.g., interest, knowledge and other personal characteristics), as well as contextual aspects, select the most appropriate content, and deliver it in the most suitable way. It should be noted that achieving this result is extremely challenging in the case of first-time users, such as tourists who visit a cultural heritage site for the first time (and maybe the only time in their life). In addition, as tourism is a social activity, adapting to the individual is not enough because groups and communities have to be modeled and supported as well, taking into account their mutual interests, previous mutual experience, and requirements. How to model and represent the user(s) and the context of the visit and how to reason with regard to the information that is available are the challenges faced by researchers in personalization of cultural heritage. Notwithstanding the effort invested so far, a definite solution is far from being reached, mainly because new technology and new aspects of personalization are constantly being introduced. This article surveys the research in this area. Starting from the earlier systems, which presented cultural heritage information in kiosks, it summarizes the evolution of personalization techniques in museum web sites, virtual collections and mobile guides, until recent extension of cultural heritage toward the semantic and social web. The paper concludes with current challenges and points out areas where future research is needed

IMPROVING THE DEPENDABILITY OF DESTINATION RECOMMENDATIONS USING INFORMATION ON SOCIAL ASPECTS

Prior knowledge of the social aspects of prospective destinations can be very influential in making travel destination decisions, especially in instances where social concerns do exist about specific destinations. In this paper, we describe the implementation of an ontology-enabled Hybrid Destination Recommender System (HDRS) that leverages an ontological description of five specific social attributes of major Nigerian cities, and hybrid architecture of content-based and case-based filtering techniques to generate personalised top-n destination recommendations. An empirical usability test was conducted on the system, which revealed that the dependability of recommendations from Destination Recommender Systems (DRS) could be improved if the semantic representation of social attributes information of destinations is made a factor in the destination recommendation process

Improving the Dependability of Destination Recommendations using Information on Social Aspects

Prior knowledge of the social aspects of prospective destinations can be very influential in making travel destination decisions, especially in instances where social concerns do exist about specific destinations. In this paper, we describe the implementation of an ontology-enabled Hybrid Destination Recommender System (HDRS) that leverages an ontological description of five specific social attributes of major Nigerian cities, and hybrid architecture of content-based and case-based filtering techniques to generate personalised top-n destination recommendations. An empirical usability test was conducted on the system, which revealed that the dependability of recommendations from Destination Recommender Systems (DRS) could be improved if the semantic representation of social attributes information of destinations is made a factor in the destination recommendation process.Content-based filtering; Recommender Systems; Ontology; Social Attributes, Destination recommendation

Context-Based Cultural Visits

Over the last two decades, there have been tremendous advances in mobile technologies, which have increased the interest in studying and developing mobile augmented reality systems, especially in the field of Cultural Heritage. Nowadays, people rely even more on smartphones, for example, when visiting a new city to search for information about monuments and landmarks, and the visitor expects precise and tailored information to his needs. Therefore, researchers started to investigate innovative approaches for presenting and suggesting digital content related to cultural and historical places around the city, incorporating contextual information about the visitor and his needs. This document presents a novel mobile augmented reality application, NearHeritage, that was developed within the scope of the master's thesis on Electrical and Computers Engineering from the Faculty of Engineering of Porto University (FEUP), in collaboration with INESC TEC. The research carried out was focused on the importance of utilising modern technologies to assist the visitors in finding and exploring Cultural Heritage. In this way, it is provided not only the nearby points-of-interest of a city but also detailed information about each POI. The solution presented uses built-in sensors and hardware of Android devices and takes advantage of various APIs (Foursquare API, Google Maps API and IntelContextSensing) to retrieve information about the landmarks and the visitor context. Also, these are crucial hardware components for implementing the full potential of augmented reality tools to create innovative contents that increase the overall user experience. All the experiments were conducted in Porto, Portugal, and the final results showcase that the concept of a MAR application can improve the user experience in discovering and learning more about Cultural Heritage around the world, creating an interactive, enjoyable and unforgettable adventure

Design of an E-learning system using semantic information and cloud computing technologies

Humanity is currently suffering from many difficult problems that threaten the life and survival of the human race. It is very easy for all mankind to be affected, directly or indirectly, by these problems. Education is a key solution for most of them. In our thesis we tried to make use of current technologies to enhance and ease the learning process. We have designed an e-learning system based on semantic information and cloud computing, in addition to many other technologies that contribute to improving the educational process and raising the level of students. The design was built after much research on useful technology, its types, and examples of actual systems that were previously discussed by other researchers. In addition to the proposed design, an algorithm was implemented to identify topics found in large textual educational resources. It was tested and proved to be efficient against other methods. The algorithm has the ability of extracting the main topics from textual learning resources, linking related resources and generating interactive dynamic knowledge graphs. This algorithm accurately and efficiently accomplishes those tasks even for bigger books. We used Wikipedia Miner, TextRank, and Gensim within our algorithm. Our algorithm‘s accuracy was evaluated against Gensim, largely improving its accuracy. Augmenting the system design with the implemented algorithm will produce many useful services for improving the learning process such as: identifying main topics of big textual learning resources automatically and connecting them to other well defined concepts from Wikipedia, enriching current learning resources with semantic information from external sources, providing student with browsable dynamic interactive knowledge graphs, and making use of learning groups to encourage students to share their learning experiences and feedback with other learners.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Luis Sánchez Fernández.- Secretario: Luis de la Fuente Valentín.- Vocal: Norberto Fernández Garcí

Topic Space: Rapid Prototyping a Mobile Augmented Reality Recommendation App

With funding from an Institute of Museum and Library Services (IMLS) Sparks! Ignition Grant, researchers from the University of Illinois Library designed and tested a mobile recommender app with augmented reality features. By embedding open source optical character recognition software into a “Topic Space” module, the augmented reality app can recognize call numbers on a book in the library and suggest relevant items that are not shelved nearby. Topic Space can also show users items that are normally shelved in the starting location but that are currently checked out. Using formative UX methods, grant staff shaped app interface and functionality through early user testing. This paper reports results of UX testing; a redesigned mobile interface, and provides considerations on the future development of personalized recommendation functionality.IMLS A0279Ope