Iterative and Semi-Supervised Design of Chatbots Using Interactive Clustering
نویسندگان
چکیده
Chatbots represent a promising tool to automate the processing of requests in business context. However, despite major progress natural language technologies, constructing dataset deemed relevant by experts is manual, iterative and error-prone process. To assist these during modelling labelling, authors propose an active learning methodology coined Interactive Clustering. It relies on interactions between computer-guided segmentation data intents, response-driven human annotations imposing constraints clusters improve relevance.This article applies Clustering realistic dataset, measures optimal settings required for minimal number annotations. The usability method discussed terms computation time, achieved compromise relevance classification performance training.In this context, appears as suitable combining computer initiatives efficiently develop useable chatbot.
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ژورنال
عنوان ژورنال: International Journal of Data Warehousing and Mining
سال: 2022
ISSN: ['1548-3924', '1548-3932']
DOI: https://doi.org/10.4018/ijdwm.298007