Comparing System-response Retrieval Models for Open-domain and Casual Conversational Agent

International audienceThis paper studies corpus-based process to select a system-response usable both in chatterbot or as a fallback strategy. It presents, evaluates and compares two selection methods that retrieve and adapt a system-response from the OpenSubtitles2016 corpus given a human-utterance. A corpus of 800 annotated pairs is constituted. Evaluation consists in objective metrics and subjective annotation based on the validity schema proposed in the RE-WOCHAT shared task. Our study indicates that the task of assessing the validity of a system-response given a human-utterance is subjective to an important extent, and is thus a difficult task. Comparisons show that the selection method based on word embedding performs objectively better than the one based on TF-IDF in terms of response variety and response length

Towards a Taxonomy of Platforms for Conversational Agent Design

Software that interacts with its users through natural language, so-called conversational agents (CAs), is permeating our lives with improving capabilities driven by advances in machine learning and natural language processing. For organizations, CAs have the potential to innovate and automate a variety of tasks and processes, for example in customer service or marketing and sales, yet successful design remains a major challenge. Over the last few years, a variety of platforms that offer different approaches and functionality for designing CAs have emerged. In this paper, we analyze 51 CA platforms to develop a taxonomy and empirically identify archetypes of platforms by means of a cluster analysis. Based on our analysis, we propose an extended taxonomy with eleven dimensions and three archetypes that contribute to existing work on CA design and can guide practitioners in the design of CA for their organizations

Utilization of Chatbots in Customer Interface

Automation has become a worldwide trend in business. Businesses try to find competitive edge from more efficient processes, lower costs and better customer service. In this Bachelor’s thesis, I focus on one instance of the trend: web-based chatbots in the customer interface. Based on a broad literature review, this thesis illustrates what are the prerequisites for the utilization of chatbots, how should they be implemented and finally, what pros and cons managers can expect from such investments. Managers should first be aware of the technical restrictions and challenges chatbots as a medium exhibit. Then, through analysis on their customers, managers should assess the suitability of chatbots for their business. The design process should include both the customers as well as different departments in the company. This can also help with change resistance in the implementation phase. Finally, the chatbot should be constantly evaluated to ensure the benefits promised are delivered. Although chatbots can offer versatility and cost savings, poorly design may end up costing the firm both in the terms of unnecessary investment and reduced customer satisfaction. Although no new concepts are introduced, this thesis is a good starting point for managers interested in utilizing chatbots. On the other hand, as the topic is currently relevant, this thesis can be useful for other industries as well