Cultural institutions today tend to favor the incorporation of mobile technologies and applications and usually o er interpretive electronic guides to their visitors, with adaptive and personalized cultural content. However, it is still unknown to what degree users approve and are satis ed with the level and depth of personalization that these technologies adopt. The purpose of this research aims to analyze the impact and quantify how personalized and obtrusive should a mobile application be and correlate these aspects with the users perception, perspective and desires. To achieve that, we propose the REPEAT methodology, that uses implicit data from users mobile device and explicit data from users answers to our REPEAT questionnaire, to categorize each visitor and assume the personalization level that ts better for his interests. Furthermore, this work will design a mobile prototype that implements the results of our research by dynamically incorporating user's feedback into the personalization process.
Nowadays, cultural institutions are consistently trying to adapt to the current
computing state of the art and integrate mobile technology and digital guides
to enhance visitors experience. As a result, galleries, libraries, archives and
museums (GLAMs) are replacing traditional passive exhibitions with interactive
displays and mobile virtual tour guides to aid visitors understanding without
overwhelming their limited physical space [
This tendency has e ectively transformed the relationship that GLAMs
maintain with their visitors, o ering unprecedented levels of access in databases with
massive information and new opportunities for interactivity that a ects
substantially Cultural User eXperience (CUX), considering the fact that Semantic Web
and Linked Open Data cloud databases have also been utilized to enrich cultural
information [
In this paper we intend to investigate the current challenges and limitations in personalization of cultural heritage information. Moreover, we propose the REPEAT methodology that classi es each visitor according to his interests and actuates the desired level of personalization. REPEAT uses data from social media and mobile sensors, while also requiring users to initially answer a small questionnaire, to estimate their pro le and adjust the digital content of the mobile guide that they may be interested in. Therefore, REPEAT exploits the functionalities of modern smartphone devices to o er e cient visiting services in a friendly manner.
The rest of the paper is organized as follows: in the rst section we present the ve categories that users are classi ed to and their characteristics according to personalization needs. The next section presents the methodology REPEAT, its questionnaire and architecture. Afterwards, we present the implementation of a mobile prototype based on the REPEAT methodology and nally, we conclude and discuss our future plans and directions. 2
Smartmuseum [
Also, Roussou et al. [
Recent articles and studies [
Explorers: Visitors who are curiosity-driven with a generic interest in the content of the museum. They visit museums without speci c targets trying to satisfy their curiosity, which is quite challenging to predict. As a result, explorers probably may not be satis ed with a strong personalization level, as they would like to nd new topics to grab their attention.
Facilitators: Visitors who are socially motivated. A personalized mobile application may not impact Facilitator's experience in a museum, because they are primarily attuned to the social aspects of the visit and don't see the museum primarily as a place for extensive personal learning and growth.
Professional/Hobbyists: Visitors who feel a close tie between the museum content and their professional or hobbyist passions. Their visits are typically motivated by a desire to satisfy a speci c content-related objective. Consequently, strong personalization is a priority for the visitors of this category.
Experience Seekers: Visitors who are motivated to visit because they perceive the museum as an important destination. Their satisfaction primarily derives from the mere fact of having been there and done that. They may not require personalized mobile guides, as their only motivation is to be in a culturally important place and have a great experience.
Rechargers: Visitors who are primarily seeking a contemplative, spiritual and/or restorative experience. They see the museum as a refuge from the worka-day world or as a con rmation of their religious beliefs. Even if they actually examine the exhibits of the museum, they often look for that special at-one experience without any particular interest in gaining additional knowledge. Therefore, personalization levels for this category should be minimum. 3.2
The cultural heritage experience is being viewed as an ongoing lifelong experience: curators and cultural researchers are continuously looking at how visitors can be captured and retained over time, both online and onsite. User personalization can play a major role by reasoning on past experience and other daily and contextual characteristics of the visitor, making the current cultural heritage experience a link in a lifelong chain. This lifelong experience through the personalized data is the basis of our methodology, which aims in identifying the user persona with the least possible user input or intervention and customize mobile guide's functionality accordingly. The data ow is shown in Figure 1 which depicts the architecture of the methodology.
Data acquisition: This stage corresponds to data acquisition from multiple
sources, either explicit or implicit (with respect to privacy and security issues).
Those sources can be organized into the following three types: (a) pro led data
derived from mobile device, social media, etc, that allow a re nement of the
associated persona, (b) user input - REPEAT questionnaire which based on our
previous analysis of Falk's ve categories of visitors [
Data reasoning: This stage includes the processing of the multiple data sources whose wide complexity and diversity will need to be modeled and reasoned. The abundance of social media user input and the subsequent opinion mining on it will allow a better user classi cation and overall the fusion of heterogeneous data streams will associate the user with a customized user persona, allowing a better understanding of the user's needs and goals.
Prior studies argue that people can play multiple roles during their
interaction with a system which can change over time, either because of interest increase
in a speci c topic, or that once the initial experience has been satis ed, users
look for what else is on o er [
As we described above, Falk identi ed ve categories of visitors based mainly on
extensive post-visit interviews which showed that these identity-related reasons
for visiting museums are a direct re ection on how the public currently perceives
the attributes and a ordances of museums; in other words, what the public
perceives as the right reasons for visiting museums [
The purpose of REPEAT questionnaire is to estimate the possibility of the user to belong in one or more of the above categories. Our original selection of questions which aimed for simple questions that will expose the basic di erences between the ve categories is shown on Figure 2.
For example, Facilitators and Explorers usually don't visit museums to seek
speci c knowledge based on the topics of each museum and their interests, since
their rst priority is to satisfy other's interests or their own curiosity respectively.
This feature strongly discriminates them from Professionals/Hobbyists, because
this category almost always enters a museum with a fairly speci c goal in mind.
Furthermore, Rechargers, Explorers and Professionals/Hobbyists are typically
repeat-visitors to their local museum while Experience Seekers are rst-time
visitors to the museum and many are relatively infrequent museum visitors.
Finally, Facilitators and Experience Seekers are motivated to visit a museum from
their desire for socialization and entertainment, while Professional's /Hobbyist's
primary motivation in visiting is typically quite speci c knowledge. Meanwhile,
Rechargers don't fall into the above categories at all, because they see museums
as places that o er them an opportunity to avoid the noisiness and clutter of
the outside world [
After the initial selection of questions, we evaluated the possible answers and removed questions which may lead us on the same results. Thus, based on our research, the not aware at all answer at the second question leads to non-signi cant results, consequently we ignore it during the nal questionnaire implementation. Subsequently, we ignored the rst question regarding the rst time visit, which can be extracted from mobile sensors and user history. 4
We designed and implemented a prototype using Proto.io in which the above issues will be examined to reach to proper conclusions and estimate the appropriate level of personalization in several occasions. Prototypes are commonly built to serve as explorative artifacts inside a vast design space, and in later phases as means to evaluate the incrementally formulated design ideas.
In gure 3, the visitor signs in the mobile guide by choosing one of his social media pro les. As we already discussed, REPEAT uses these pro les to identify possible interests and thus adjust the context of the mobile guide. Thus, user's registration is a basic feature of the REPEAT module. Afterwards, the visitor answers a questionnaire that will classify him in the ve categories analyzed above. The questions are as few as possible and easy to be answered, as we don't want to distract visitors from their cultural experience. Figure 3 also depicts the personalized content as a result of the REPEAT methodology, based on the museum's topics. The visitor can change his personalization level by selecting other tasks which are based on the next most probable estimated pro le category. 5
Through our REPEAT methodology, we were able to elicit the technology and user personalization needs regarding cultural areas. This study provides the justi cation needed for the implementation of a personalized methodology for a cultural space that attempts to satisfy the needs of the users. The proposed methodology will help the visitors understand how and how much the cultural space can meet and satisfy their individual identity-related needs.
In our study, we have extended the already existing work by designing new user personalization methods. In retrospect, we trust that our choice of research methods and process can also be used for the UX evaluation of other technology concepts that are futuristic and novel. Also, our contribution will help the cultural spaces to make changes in the nature of what they o er to the public that are more consistent with the perceived needs of their visitors and increase their institutional value by applying the principles of the proposed module to everyday practice.
In the future, we will use this personalized methodology as a basis to design the frontend and backend components of the REPEAT module. Furthermore, our next step is the implementation of the module in a cultural mobile application of an institution and a formative evaluation with prospective users and a redesign cycle to ensure that the mobile user interface adequately supports user's needs, and also check the e ciency, validity and reliability of the questionnaire proposed. The module will be implemented with a strong feedback mechanism that will request user opinion about ease of use, potential usefulness, persona's identi cation accuracy user satisfaction and intrusion level etc., allowing for a semi-automated customization procedure towards a more satisfactory Cultural UX overall. 6
The research and writing of this paper was nancially supported by the General Secretariat for Research and Technology (GSRT) and the Hellenic Foundation for Research and Innovation (HFRI). John Aliprantis has been awarded with a scholarship for his PhD research from the 1st Call for PhD Scholarships by HFRI Grant Code 234.
Konstantakis et al.