Exploring Conversational Language Generation for Rich Content about Hotels
Table 6: Attributes Frequently Grouped in a Single Turn
['[BOLD] Attribute Group', '[BOLD] Count']
Results. We begin by analyzing information that both the dialogue manager and the natural language generator would need to know, namely how frequently attributes are grouped in a single turn in our collected dialogues, by counting the number of times certain keywords are mentioned related to the attributes in the dialogues. We note that the attributes within the groups are generally either: 1) semantically similar, e.g. ”modern” and ”contemporary”; 2) describe the same aspect, e.g. ”feels elegant” and ”feels upscale”; or 3) describe the same general attribute, e.g. ”has breakfast buffet”, ”has free breakfast”, and ”has free breakfast buffet”. It is interesting to note that the semantic similarity is not always completely obvious (for example, ”has balcony in rooms” and ”has fireplace” may be used to emphasize more luxurious amenities that are a rare find).