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| An Extended Belief Network Retrieval Model Based on Document Relationships |
| Xu Jianmin1, He Dandan1, Wu Shufang2 |
1.College of Cyberspace Security and Computer, Hebei University, Baoding 071002
2.School of Management, Hebei University, Baoding 071002 |
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Abstract The performance of a retrieval model can be improved by using relationships among documents reasonably. To solve the problem of a basic retrieval model that does not use document relationships, an extended belief network retrieval model with two layers of document nodes is proposed. The topology structure and probability inference of the extended model are given. In the topology structure, relationships between items like terms and queries, terms and documents, and two layers of documents, are indicated by arcs. The relationship between documents is determined by the similarity of the documents. In the probability inference, the retrieval probability is made more accurate by using document similarity and the number of parent documents to modify the original probability. In experiments, the value of discounted cumulative gain and the precision-recall curve are introduced to attest to the performance of our proposed extended model. The results show that the extended model makes the ranking of related documents more reasonable and improves the precision under the premise of guaranteeing recall.
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Received: 12 December 2018
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