Microsoft Technology Licensing, LLC

Daxin Jiang

Linjun Shou

Ming Zhou

Hang Li

Xin Zhang

Yang Yang

Yi Zeng

Shujie Liu

Nan Duan

Duyu Tang

Xuguang Wang

Ming Gong

Wendi Wang

Siming Tian

Xuanyu Bai

The present disclosure proposes a method and apparatus for multi-model joint denoising training. Multiple models may be obtained. A set of training samples may be denoised through the multiple models. The multiple models may be trained with the set of denoised training samples.

Multi-model joint denoising training

The present disclosure provides method and apparatus for query conversion. A first query for a first graph database may be obtained. A syntax tree may be generated through parsing the first query. A query graph may be created based on the syntax tree. The query graph may be converted into a second query for a second graph database.

Query conversion for different graph query languages

In embodiments of the present disclosure, there is provided an assertion-based question answering manner. After a question and the related passage are obtained, an assertion answer to the question is determined based on content of the passage, and the assertion answer has a predetermined structure and represents a complete semantic meaning. Then, the assertion answer to the question may be outputted to the user. In the embodiments of the present disclosure, the question and the relevant passage are used as input, and a semi-structured assertion answer is output. The assertion answer according to embodiments of the present disclosure can provide richer semantic content than the traditional short answer, and provide a more concise expression than the traditional long answer, thereby ensuring accuracy of the answer while improving the user experience.

Assertion-based question answering

Techniques described herein describe a context-aware query suggestion process. Context of a current query may be calculated by analyzing a sequence of previous queries. Historical search data may be mined to generate groups of query suggestion candidates. Using the context of the current query, the current query may be matched with the groups of query suggestion candidates to find a matching query suggestion candidate, which may be provided to the user.

Context-aware query suggestion by mining log data

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Daxin Jiang