# 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
All aspects were evaluated using subjective expression of opinions, via the questionnaire illustrated in Table 4. Willingness to use the chatbot was also explored via objective observations, through the actual self-motivated involvement of the subject in the exploration of additional narratives, beyond the tasks that the subjects were requested to complete. Thirty-eight persons took part in the chatbot use evaluation survey. The participants were initially briefed for approximately four minutes on the use of the chatbot (presentation of the overall navigation structure, explanation of the narrative concept, and introduction of chatbot interaction and controls), and were then requested to choose and follow one narrative. Participants were allowed to select and follow a second narrative if they wished to. After the experience, participants were requested to complete a questionnaire. All participants completed the first narrative, and six of the participants proceeded to traversing the second one. Users found the chatbot easy to use (average: 4.24, standard deviation: 0.75, and min: 2; max: 5), and that dialogues flowed fluidly (average: 4.03, standard deviation: 0.78, min: 2, and max: 5). The user interface was also found to be intuitive (average: 4.34, standard deviation: 0.63, max: 5, and min: 3) and quite pleasant (average: 3.87, standard deviation: 0.66, min: 2, and max: 5). The pleasant user interface criterion received the lowest marks, indicating that a more sophisticated user interface implementation is required. Ten users exploited the functionality of skipping additional exhibit details when information about an exhibit was split into chunks, i.e., they only viewed the first screenful of exhibit information and then moved to the next exhibit. Finally, users stated that they would like to follow additional narratives to explore additional content, including different aspects of exhibits they had already viewed (average: 4.45, standard deviation: 0.60, max: 5, and min: 3). \begin{table}
\begin{tabular}{c} \hline \hline
**Question** \\ \hline The chatbot was easy to use \\ \hline The dialogues with the chatbot were fluid \\ \hline The user interface was intuitive \\ \hline The user interface was pleasant \\ \hline I would like to use the chatbot further to explore additional content and narratives \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Questionnaire for assessing the subjective aspects of the chatbot use. ## 4 Discussion

The proposed work advances the state of the art by providing a framework through which chatbots can provide full guidance and a complete museum experience conveying the intended museum message, in contrast to supporting ad hoc queries for individual exhibits or fragmented experiences. It is also worth noting that the proposed approach is based on the theoretical framework of narratives, which formalizes the successful practice used by human museum guides, and has also been defined and successfully tested [39; 40]. Additionally, the proposed approach accommodates the multiple facets of museum exhibits, which can be organized under different itineraries with specifically tailored storytelling and exhibit sequences. Furthermore, an algorithm is presented to automate museum chatbot generation, allowing the museums to create and maintain their own chatbots in a code-free environment. This algorithm utilizes the DialogFlow chatbot engine, directly exploiting all available features including augmented user interfaces and natural speech-based interaction. The methodology presented in this paper has both practical and research implications. Practitioners and professionals may use the proposed methodology to construct chatbots for museums with low effort and cost. This is of particular importance for small- and medium-sized museums where budget is limited and IT personnel resources are scarce. The automation of the chatbot creation procedure can relieve the museum staff from a tedious and uninteresting task, necessitating, however, the introduction of a narration modeling application.