Hybrid Q&A Method for Knowledge Graph and Documents of Global Petroliferous Basins

The massive data and information in the petroliferous basins formed by exploration and development are extremely valuable. Thus, they need to be deeply mined and utilized by new technologies to provide data support and decision basis for exploration and development. The knowledge graph can well integrate the knowledge contained in these data and documents. However, its concept and relationship rely on manual construction, which results in its limited coverage of knowledge areas. The traditional question-and-answer (Q&A) method can get relevant answers from documents according to questions, which has the characteristics of wide knowledge coverage. Nevertheless, it is difficult to understand the contents of professional fields, which leads to its low accuracy in petroliferous basins. In order to address the above problems, this paper proposes a hybrid Q&A method for merging the knowledge graph and documents in petroliferous basins. The method takes the knowledge graph of petroliferous basins as the knowledge base of professional background. Additionally, it obtains professional-related knowledge contents from documents. In particular, to answer the question on petroliferous basins, the method firstly extracts entities from the question according to the knowledge graph. Then, with these entities, the method converts the question into a query in the knowledge graph, obtaining partial candidate answers to the question. For obtaining candidate answers from documents, the method constructs a deep semantic matching model which incorporates knowledge graph embedding. The model can match the question and answers in documents base on the information from the knowledge graph. Finally, the method leverages a sort algorithm to reorder the above two types of candidate answers from the knowledge graph and documents respectively. Compared with traditional Q&A methods, the hybrid Q&A method supports professional Q&A scenarios for the knowledge graph and documents of petroliferous basins, improving the efficiency of users’ knowledge query and increasing the recall rate while ensuring the retrieval accuracy. The hybrid Q&A method has the characteristics of convenient operation, strong interaction and high accuracy, etc., which provides a platform on knowledge deep sharing and application for the study of petroliferous basins.