BERT for Conversational Question Answering Systems Using Semantic Similarity Estimation

Most of the questions from users lack context needed to thoroughly understand problem at hand, thus making impossible answer. Semantic Similarity Estimation is based on relating user’s previous Conversational Search Systems (CSS) provide answers without requesting user's context. It imposes constraints time produce an answer for user. The proposed model enables use contextual data associated with Searches (CS). While receiving a question in new conversational search, determines that refers more past CS. then infers related given and predicts inferred engaging multi-turn interactions or additional user This shows ability limited information queries best inferences Closed-Domain-based CS Bidirectional Encoder Representations Transformers textual representations.