Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (4): 910-915.doi: 10.13229/j.cnki.jdxbgxb20210025

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Text information similarity search algorithm based on segment estimation and PageRank

Ling ZHAI1(),Xu CUI2()   

  1. 1.Department of Library Information Technology，Xi'an University of Science and Technology，Xi'an 710054，China
    2.School of Public Management，Northwest University，Xi'an 710027，China
  • Received:2021-01-19 Online:2022-04-01 Published:2022-04-20
  • Contact: Xu CUI E-mail:zhaillll1@163.com;zhai13909282219@163.com

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Abstract:

Because the current existing methods fail to consider the problem of text information feature extraction， the average relevance， average excellence rate and new word search accuracy rate decrease. In order to effectively solve the above problems， a text information similarity search algorithm based on segment estimation and PageRank is proposed. First， the segmentation estimation method is used to extract text features， and the PageRank value is taken as the criterion for preliminary classification of text information. Then， the similarity of different features of text information is calculated， the text information similarity is sorted. Finally， the similarity is searched based on the relevance between text information， effectively realizing the similarity search of text information. Simulation results show that the proposed algorithm can comprehensively improve the average correlation， average excellence rate and new word search accuracy， and the highest new word search accuracy reaches 98.98%， which indicates that the algorithm can obtain high quality and high stability search results.

Key words: segment estimation, PageRank, text information, similarity search

CLC Number: 

  • TP391

Fig.1

Local extremum points and fluctuating points"

Fig.2

Vector space model"

Fig.3

Flow chart of text information similarity search"

Table 1

Search content library"

搜索类别搜索数量/个
总数1500
含有新词50
复杂搜索700
简单搜索750

Fig.4

Average correlation comparison results of different algorithms"

Fig.5

Comparison results of average excellence rate of different algorithms"

Table 2

Comparison results of new word search accuracy of different algorithms"

新词数量/个不同算法新词搜索准确率/%
本文文献［3］文献［4］
1098.9896.8595.63
2097.5895.3693.85
3097.4594.1492.74
4096.2592.2591.33
5096.3692.5590.74
6095.4191.7488.39
7095.2090.3687.85
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