Text Retrieval Based on Syntactic Information

被引：0
|
作者：
Yongwei Z. [1 ,2 ]
Ting L. [1 ]
Chang L. [3 ]
Bingxin W. [3 ]
Jingsong Y. [3 ]
机构：
[1] School of Chinese Language and Literature, University of Chinese Academy of Social Sciences, Beijing
[2] Corpus and Computational Linguistics Center, Institute of Linguistics, Chinese Academy of Social Sciences, Beijing
[3] School of Software and Microelectronics, Peking University, Beijing
来源：
Data Analysis and Knowledge Discovery | 2022年 / 6卷 / 11期
关键词：
Constituency Syntax; Corpus; Dependency Syntax; Index; Retrieval;
D O I：
10.11925/infotech.2096-3467.2022.0093
中图分类号：
学科分类号：
摘要：
[Objective] This study aims to explore an efficient method for retrieving syntactic information from large text corpora. [Methods] First, we created linearized indices for syntactic information based on their features. Then, these indices provide matching information to improve retrieval efficiency. [Results] We examined our new model with the People’s Daily Corpus of 28.51 million sentences. The average processing time for 26 queries was 802.6 milliseconds, which met the requirements of retrieval systems for large corpora. [Limitations] More research is needed to evaluate the proposed method with larger number of queries. [Conclusions] Our new method could quickly retrieve lexical, dependency syntactic and constituency syntactic information from large text corpora. © 2022, Chinese Academy of Sciences. All rights reserved.
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页码：25 / 37
页数：12
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