Constructing and analyzing intention knowledge graphs

Cheng CHEN; Yueguo CHEN; Chen LIU; Xiaotong LYU; Xiaoyong DU

doi:10.11959/j.issn.2096-0271.2020014

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Constructing and analyzing intention knowledge graphs

Topic:government governance big data | 更新时间：2024-06-03

- Constructing and analyzing intention knowledge graphs
- Big Data Research Vol. 6, Issue 2, Pages: 2020014-1(2020)
- 作者机构：
  
  1. 中国人民大学数据工程与知识工程教育部重点实验室，北京 100872
  2. 中国人民大学信息学院，北京 100872
  3. 中国人民大学统计学院，北京 100872
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2020014
  CLC： TP391
- Online First：2020-03，
  
  Published：15 March 2020
- 稿件说明：
移动端阅览
Cheng CHEN, Yueguo CHEN, Chen LIU, et al. Constructing and analyzing intention knowledge graphs[J]. Big Data Research, 2020, 6(2): 2020014-1.
DOI：

Cheng CHEN, Yueguo CHEN, Chen LIU, et al. Constructing and analyzing intention knowledge graphs[J]. Big Data Research, 2020, 6(2): 2020014-1. DOI： 10.11959/j.issn.2096-0271.2020014.

摘要

政府治理的效果评估是一个难题。没有很好的评估方法和评估体系，政府治理的效果就不能得到很好的保障。提出从自然语言问答的角度理解网民在政府治理话题中的意图，并通过构建意图知识图谱，关联语义等价的问题和意图。不同意图又通过实体的相互关联，支持意图的关联和对比。给出了意图知识图谱的定义、构建框架和政府治理场景的使用范例，展示了意图知识图谱是解决政府治理的效果评估问题的一种有效方法。在政府治理的场景中，利用意图知识图谱可以分析对比同一治理话题下不同治理主体之间的意图场，从而深入剖析特定治理主体在特定治理话题下的效果，并发现治理中存在的问题。

Abstract

It is very difficult to evaluate the effects of government governance.Without a good evaluation method and evaluation system

the effects of government governance cannot be guaranteed.Understanding the intention of web users in the topic of government governance from the perspective of natural language question-and-answering was proposed.By constructing a knowledge graph of intentions

equivalent questions and intentions were associated.The definition

construction framework and usage examples in government governance were illustrated

showing that knowledge graph of intentions is an effective way to evaluate the effects of government governance.In the context of government governance

by using the knowledge graphs of intentions

the intention fields between different governance subjects under the same governance topic were analyzed and compared

the effects of specific governance subjects on specific governance topics were analyzed

and the issues remained in government governance were found.

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references

NOVAK B , . A survey of focused web crawling algorithms [C ] // SIKDD,October 15,2004,Ljubljana,Slovenia . New York:ACM Press , 2004 : 55 - 58 .

LEE T , WANG Z Y , WANG H X , et al . Attribute extraction and scoring:a probabilistic approach [C ] // 2013 IEEE 29th International Conference on Data Engineering,April 8-11,2013,Brisbane,Australia . Piscataway:IEEE Press , 2013 : 194 - 205 .

TATAR S , CICEKLI I . Automatic rule learning exploiting morphological features for named entity recognition in Turkish [J ] . Journal of Information Science , 2011 , 37 ( 2 ): 137 - 151 .

PETASIS G , VICHOT F , WOLINSKI F , et al . Using machine learning to maintain rule-based named-entity recognition and classification systems [C ] // The 39th Annual Meeting on Association for Computational Linguistics,July 6-11,2001,Toulouse,France.[S.l] .: ACL , 2001 : 426 - 433 .

DEVLIN J , CHANG M W , LEE K , et al . Bert:pre-training of deep bidirectional transformers for language understanding [J ] . Computer Science 2018 ,arXiv:1810.04805.

范举 , 陈跃国 , 杜小勇 . 人在回路的数据准备技术研究进展 [J ] . 大数据 , 2019 , 5 ( 6 ): 3 - 18 .

FAN J , CHEN Y G , DU X Y . Progress on human-in-the-loop data preparation [J ] . Big Data Resreach , 2019 , 5 ( 6 ): 3 - 18 .

ANTUNES F , FREIRE M , COSTA J P . Semantic web and decision support systems [J ] . Journal of Decision Systems , 2016 , 25 ( 1 ): 79 - 93 .

VARELAS G , VOUTSAKIS E , RAFTOPOULOU P , et al . Semantic similarity methods in wordNet and their application to information retrieval on the web [C ] // The 7th Annual ACM International Workshop on Web Information and Data Management,November 19-23,2005,Bremen,Germany . New York:ACM Press , 2005 : 10 - 16 .

IDREOS S , PAPAEMMANOUIL O , CHAUDHURI S . Overview of data exploration techniques [C ] // The 2015 ACM SIGMOD International Conference on Management of Data,May 31-June 4,2015,Melbourne,Australia . New York:ACM Press , 2015 : 277 - 281 .

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