Analyzing the Digital Brains of Virtual Assistants

Abstract—In this paper, we analyze the digital brains of virtual assistants by reviewing their inner workings of learning and thinking. We review the process for creating the digital brains (knowledgebase and inference engine) by focusing on knowledge acquisition (learning) and knowledge discovery (thinking). We then attempt to extend the ability of virtual assistants by allowing them to read and write. To read documents conceptually in order to write abstractive summaries, our system makes use of one of the world’s largest knowledgebases and one of the most powerful inference engines. The resultant AI system first uses natural language processing techniques to extract syntactic structure of the documents and then maps the words of the sentences and their parts of speech into related concepts in the knowledgebase. It then uses the inference engine to generalize and fuse concepts to form more abstract concepts. The system then composes new sentences based on the key concepts by linking subject concepts with their related predicate concepts. The system has been implemented and tested. The test results showed that the system can create new sentences that include abstracted concepts not explicitly mentioned in the original documents and that contain information synthesized from different parts of the documents to compose a summary.
 
Index Terms—knowledgebase, natural language processing, knowledge engineering.

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Cite: Ann Clifton and Ben Choi, "Analyzing the Digital Brains of Virtual Assistants," International Journal of Knowledge Engineering vol. 9, no. 2, pp. 21-26, 2023.

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).