Comprehensive Technology Function Product Matrix for Intelligent Chatbot Patent Mining

Abstract

Conversational intelligence and the rise of its agent through “chatbots” are disrupting businesses worldwide. Chatbots enable natural interactions via text or voice leveraging technologies. Chatbots are used for various practical purposes such as information acquisition, customer service, and virtual assistance. Google Assistant, Apple Siri, and Amazon Alexa are some of the most widely used virtual assistants. Further, several use cases demonstrate a customer preference for chatbot interface against conventional graphical user interfaces. This has led to rapid growth in chatbot research and consecutively has led to a growth in the filing of patents. The disclosed patents represent major advances in the technology and offer hints about the directions conversational chatbots will grow in the future. Businesses wanting to integrate chatbot technology must, therefore, conduct an exhaustive patent analysis to identify required technologies, functions, and their associated product applications. This research presents a text mining based Technology Function Product Matrix (TFPM) generation approach to analyze a corpus of more than 400 chatbot technology patent documents. The analysis systematically identifies hotspot distributions across the patent landscape with respect to the key technologies, functional advances, and novel applications as current developments in chatbot technologies.

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