Improved vector space model based on document relationships

doi:10.3969/j.issn.1000-1565.2020.03.014

Abstract

Abstract: Due to insufficient user query information, the retrieval results of traditional vector space model are not accurate enough. To solve this problem, an improved vector space model based on document relationship is proposed. The improved model combines the related documents ranked first in the initial retrieval results into a benchmark set. By calculating the similarity between each document in the initial retrieval result set and the benchmark set, the similarity between documents and queries in the original model and reorder the retrieval results is corrected, thus improving the vector space model.The experimental results show that, compared with the traditional vector space model, the improved model makes the ranking of related documents more reasonable and improves the precision while ensuring the recall rate.

Key words: document relationship, vector space model, document similarity, information retrieval

CLC Number:

TP391

HE Dandan,WU Shufang,XU Jianmin. Improved vector space model based on document relationships[J]. Journal of Hebei University (Natural Science Edition), 2020, 40(3): 322-327.

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