JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2018, Vol. 53 ›› Issue (3): 30-35.doi: 10.6040/j.issn.1671-9352.1.2017.012

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Fusion of pointwise and deep learning methods for passage ranking

PANG Bo*, LIU Yuan-chao   

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, Heilongjiang, China
  • Received:2017-09-07 Online:2018-03-20 Published:2018-03-13

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Abstract: Intelligent question answering is an important way to make information acquisition more intelligent and convenient. Intelligent Q&A oriented passage ranking is very important for accurately grasping the user's query intention, improving the user experience and the accuracy of feedback. We use deep learning techniques to capture semantic information about query and passages, and build the mapping model to the tag. Then the training model is used to predict the correlation between new query and the passage. Finally, we use the predicted correlation index of the passages and the query to sort the multiple answers of the same question. The experimental results show that our method can reach 3.979 on DCG@3 and 5.396 for DCG@5.

Key words: deep learning, passage ranking, relevance

CLC Number: 

  • TP391.1
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