Emerging Technologies of Natural Language‐Enabled Chatbots: A Review and Trend Forecast Using Intelligent Ontology Extraction and Patent Analytics

Abstract

Natural language processing (NLP) is a critical part of the digital transformation. NLP enables user-friendly interactions between machine and human by making computers understand human languages. Intelligent chatbot is an essential application of NLP to allow understanding of users’ utterance and responding in understandable sentences for specific applications simulating human-to-human conversations and interactions for problem solving or Q&As. This research studies emerging technologies for NLP-enabled intelligent chatbot development using a systematic patent analytic approach. Some intelligent text-mining techniques are applied, including document term frequency analysis for key terminology extractions, clustering method for identifying the subdomains, and Latent Dirichlet Allocation for finding the key topics of patent set. This research utilizes the Derwent Innovation database as the main source for global intelligent chatbot patent retrievals.

Natural Language Processing Patents Landscape Analysis

“…Regarding the NLP topics or sub-domains that are most applied for and researched, this study found that the field of speech recognition is gaining an increasing interest in research and invention activities, which is supported by the findings of Chao et al in [8]. The growing enthusiasm for speech recognition could be attributed to the recent commercial hype about personal assistants, such as Siri, and other conversational AI products.…”

“…When it comes to NLP patent analysis, Chao et al in [8] provided a comprehensive study of the emerging technologies in the field of NLP with an intense focus on exploring the technological developmental trends of NLP-enabled intelligent chatbots. The study adopted several text-mining techniques, such as document term frequency analysis (TF-IDF) to identify the key terminologies used in NLP patents, clustering methods to analyze the sub-domains of NLP that have a higher application rate in patents, and Latent Dirichlet Allocation for topic modeling to extract the key topics in the patent dataset.…”

Text Mining Approaches Oriented on Customer Care Efficiency

“…The use of chatbot in combination with Customer Relationship Management -CRM-can improve the ability of the company to offer information towards its clients (Setiawan, et al, 2019). The efficacy of chatbots is a function of the Natural Language Processing -NLP-algorithm adopted for the development (Chao, et al, 2021): Convolutional Neural Networks-CNN-and Long Short-Term Memory-LSTM- (Massaro, et al, 2021) algorithms can be applied to optimize the recognition of words and phrases and a combination of questions and answers. The application of NLP in chatbot systems can also improve the efficacy of health assistance as for telemedicine applications (Omoregbe, et al, 2020).…”

The effects of artificial intelligence on the Kenyan society

“…Customer support chatbots are becoming increasingly commonplace. There is renewed curiosity in chatbots because of NLIs [19], [20]. Customers can type in questions and get clear responses in natural language because of chatbots' human-like dialogue [21].…”

“…The functionality of AI allows apps to learn from every user and their behavior [38], [39]. Through their mobile app, Tala screens loan applicants with little to no credit history and disburses funds [20], [21], [36]. The program allows the company to evaluate these previously ineligible clients by calculating their default risk based on Meta and S-M-S facts [12], [15]- [19], [22], [25], [39], [40].…”