International Business Machines Corporation

Yan Fei Wang

Qi Cheng Li

Xin Zhou

Shiwan Zhao

Yi Qin Yu

Jing Mei

Lijun Mei

Yuan Zhou

Xu Min

Xue Han

Aspects of the invention include a computer-implemented method including extracting a domain-specific object feature from a first image data, wherein the feature describes an object in the first image data. A domain-specific semantic meaning of text data is determined. The object feature is mapped to a portion of the text data, wherein the portion of the text data describes the object. A joint representation of the object and the portion of the text data is created. A second image data and a query directed towards an object in the second image data is received. An answer to the query is generated based on the joint representation.

Medical visual question answering

A chatbot system receives utterances of a conversation. The chatbot system constructs a conversation knowledge graph comprising one or more dialogue segments that correspond to utterances of the conversation. The chatbot system identifies a dialogue segment in the conversation knowledge graph having a contextual uncertainty that is detected based on a context model. The chatbot system generates a clarifying question for the identified dialogue segment having the contextual uncertainty. The chatbot system receives a clarifying answer from a user interface of the computing device to the clarifying question. The chatbot system updates the context model and the conversation knowledge graph based on the clarifying question and the clarifying answer to resolve the contextual uncertainty of the identified dialogue segment.

Conversation-based chatbot training

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Shanghai, China

Yan Fei Wang