# Chatots for Cultural Venues: A Topic-Based Approach
## 2 Materials and Methods
### Mapping of Structured Information to Google DialogFlow Elements
#### 2.3.2 Automating Mapping of Data to DialogFlow Information Elements
Funerary art;* Man-made objects;
* Reliefs;
* Sculptures;
* Tombstones;
* Tondi (circular sculptures);
* Votive offerings. The steps that were followed to realize the chatbot were as follows:
* The material that had been prepared for the narratives of the museum in the context of developing a digital application were studied and the three most prominent reflective topics for implementation within the chatbot engine were chosen. * The exhibit type dimension was also selected for implementation, as this was considered to be the most comprehensible for users. * The methodology presented in Section 2.2 was followed to create the chatbot. All features listed in Section 2.2 were accommodated in the implementation, i.e., (a) presentation of the museum profile; (b) selection of the narration axis/dimension that will be followed (specific reflective topic or specific exhibit type); (c) traversing of the chosen narration axis; (d) ability to skip detailed presentation of an exhibit and move directly to the next one; and (e) ability to return to the start of a narration axis. Additionally, as listed above, the Kommunicate user interface was integrated on top of the DialogFlow engine, to offer a more interactive and user-friendly environment. Figure 12 illustrates the overall mode of interaction of users with the chatbot. Figure 13 illustrates the chatbot dialogues for listing and selecting itineraries (a) according to the exhibit type and (b) reflective topic. Figure 12: User interaction with the chatbot. Figure 13: (a) List of exhibit types, (b) list of reflective topics. Figure 14 presents chatbot dialogues excerpts for (a) displaying the description of an exhibit category according to the exhibit type and its contents and (b) displaying details about an exhibit within the category. Finally, Figure 15 presents the chatbot dialogues excerpts for (a) selecting a reflective topic and displaying the introductory information and (b) displaying information about an exhibit in the itinerary related to the reflective topic. ### Evaluation

In order to gain insight to the user's perception on the chatbot, we conducted two user studies: one aimed towards assessing the chatbot creation process and one aimed towards evaluating the chatbot use. The results of these studies are presented in the following two subsections. Figure 14: (a) Selecting the first type of exhibits (status), (b) displaying detailed information about an exhibit. Figure 15: (a) Selecting the ‘Education’ reflective topic, (b) displaying detailed information about an exhibit. #### 3.2.1 Evaluation of the Chatbot Creation Process

The first part of the evaluation was targeted to the stakeholders involved in the chatbot creation process. For the determination of the aspects to be evaluated and the formulation of the pertinent questionnaire, relevant public service creation user surveys were considered [47; 48]; in particular, the aspects of learnability, efficiency, memorability, few errors and satisfaction were discerned as relevant for inclusion in this evaluation. The aspects of \"few errors\" and \"efficiency\" were measured as objective parameters, counting the number of mistakes made in the process and the time needed to perform the assigned task, respectively; the remaining aspects were assessed via subjective expression of opinion through the questionnaire illustrated in Table 3.

In this evaluation, four participants were asked to perform a part of the chatbot creation process and express their opinion regarding the different aspects of this process. Two participants were postgraduate students of cultural studies, one participant was a graduate of humanistic studies and one of them was a postgraduate student of computer science. None of them had prior experience with using the DialogFlow console. The participants were first introduced to the DialogFlow console, covering only the agent (chatbot) creation and the intent creation steps. Participants were instructed to ignore the other elements of the DialogFlow console, including the entities and knowledge menus.