scholarly journals Reconstruction of ER Network from Specific Academic Texts for the Governance of MSW-NIMBY Crisis in China

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Qing Yang ◽  
Hui Zhou ◽  
Xingxing Liu ◽  
Chen Zuo ◽  
Jinmei Wang
Keyword(s):  
Extraction Method ◽  
Knowledge Integration ◽  
Semantic Analysis ◽  
Crisis Response ◽  
Remedial Action ◽  
Rule Based ◽  
Academic Texts ◽  
Governance Strategies ◽  
Modernization Process ◽  
Entity Relationship

Along with urban development globally, the NIMBY (Not-In-My-Backyard) crisis has been a complex social problem, which requires urgent remedial action. The inevitable management of Municipal Solid Waste (MSW) has been one of the toughest risk management tasks in the worldwide modernization process. At present, certain fuzzy and unstructured results and methods have been formed for MSW-NIMBY crisis response, mainly focusing on the sociology and politics which scatter in complex and sensitive reports and news. Aiming at enhancing the effectiveness of data mining from specific sparse text of MSW-NIMBY crisis, an improved knowledge extraction method is developed. Through rule-based text mining and complex network analysis, the Entity Relationship (ER) network of MSW-NIMBY crisis is reconstructed. Meanwhile, a novel transitivity for relationship between entities in semantic analysis is proposed to improve the feasibility and accuracy of information extraction. Characteristics and regularity of MSW-NIMBY crisis evolution and experience of crisis governance could be identified effectively. Results show that knowledge integration and ER transitivity can enhance knowledge recognition and major other factors, which could help formulate the governance strategies of NIMBY crisis from academic texts.

scholarly journals A Novel Chinese Entity Relationship Extraction Method Based on the Bidirectional Maximum Entropy Markov Model

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Chengyao Lv ◽  
Deng Pan ◽  
Yaxiong Li ◽  
Jianxin Li ◽  
Zong Wang
Keyword(s):  
Markov Model ◽  
Maximum Entropy ◽  
Extraction Method ◽  
Semantic Analysis ◽  
Short Term Memory ◽  
Knowledge Bases ◽  
Relationship Extraction ◽  
Intelligent Information ◽  
Entity Relationship ◽  
The Relationship

To identify relationships among entities in natural language texts, extraction of entity relationships technically provides a fundamental support for knowledge graph, intelligent information retrieval, and semantic analysis, promotes the construction of knowledge bases, and improves efficiency of searching and semantic analysis. Traditional methods of relationship extraction, either those proposed at the earlier times or those based on traditional machine learning and deep learning, have focused on keeping relationships and entities in their own silos: extracting relationships and entities are conducted in steps before obtaining the mappings. To address this problem, a novel Chinese relationship extraction method is proposed in this paper. Firstly, the triple is treated as an entity relation chain and can identify the entity before the relationship and predict its corresponding relationship and the entity after the relationship. Secondly, the Joint Extraction of Entity Mentions and Relations model is based on the Bidirectional Long Short-Term Memory and Maximum Entropy Markov Model (Bi-MEMM). Experimental results indicate that the proposed model can achieve a precision of 79.2% which is much higher than that of traditional models.

New-style Banks and The Agent Governance Strategies of the Beiyang Government: A Study on the History of the Development of China's Documentary Railway Billing Business in Modern Times

2021 ◽  
Vol 7 (5) ◽  
pp. 501-519
Keyword(s):  
Modern China ◽  
Weak State ◽  
Railway Freight ◽  
Governance Model ◽  
Governance Strategies ◽  
History Of ◽  
State Regime ◽  
The Republic ◽  
Modernization Process ◽  
Reform Model

Under the "weak state" regime of modern China, it was difficult for the country’s modernization process to develop without the effective intervention of a centralized state. In the process of government governance, absorbing social organizations and civil forces as agents had proved to be an effective method. Beiyang government’s governance strategy of ‘using agents to regulate agents’ in the documentary railway billing business could be regarded as typical of the diversity of government management. Qing Dynasty, government departments were not directly responsible for railway freight for various reasons, instead, they allowed railway transshipment companies to act as agents for freight management. Then transshipment companies gradually became an obstacle to Beiyang government’s reform on freight transport. However, under the Republic of China, the new-style bank discovered a benign opportunity to develop documentary railway billing service and created a bottom-up institutional reform model. Through the service, the bank became the new agent for the supervision of the transshipment company, which not only regulated the operation, but also forced railroad bureaus in the Yangzi Delta to be primarily responsible for railway freight. The Central Ministry of Transportation of Beiyang Government decided to promote this agency governance model and billing service nationwide. Received 11th January 2021; Revised 2nd June 2021; Accepted 20th July 2021

scholarly journals A Community Extraction Method using Intersection Graph and Semantic Analysis in Complex Network

2013 ◽  
Vol 25 (1) ◽  
pp. 540-555 ◽  
Author(s):  
Toshiya KURAMOCHI ◽  
Naoki OKADA ◽  
Kyohei TANIKAWA ◽  
Yoshinori HIJIKATA ◽  
Shogo NISHIDA
Keyword(s):  
Complex Network ◽  
Extraction Method ◽  
Semantic Analysis ◽  
Intersection Graph ◽  
Community Extraction

scholarly journals A Rule-based Conversion of an EER Schema to Neo4j Schema Constraints

2021 ◽  
Author(s):  
Telmo Henrique Valverde da Silva ◽  
Ronaldo dos Santos Mello
Keyword(s):  
Data Model ◽  
Design Methodology ◽  
A Priori ◽  
Database Management System ◽  
Conversion Process ◽  
Graph Database ◽  
Graph Databases ◽  
Rule Based ◽  
Promising Solution ◽  
Entity Relationship

Several application domains hold highly connected data, like supply chain and social network. In this context, NoSQL graph databases raise as a promising solution since relationships are first class citizens in their data model. Nevertheless, a traditional database design methodology initially defines a conceptual schema of the domain data, and the Enhanced Entity-Relationship (EER) model is a common tool. This paper presents a rule-based conversion process from an EER schema to Neo4j schema constraints, as Neo4j is the most representative NoSQL graph database management system with an expressive data model. Different from related work, our conversion process deals with all EER model concepts and generates rules for ensuring schema constraints through a set of Cypher instructions ready to run into a Neo4j database instance, as Neo4J is a schemaless system, and it is not possible to create a schema a priori. We also present an experimental evaluation that demonstrates the viability of our process in terms of performance.

scholarly journals User Acceptance Evaluation of a Gamified Knowledge Sharing Platform for Use in Industrial Environments

2019 ◽  
Vol 6 (2) ◽  
pp. 89-108 ◽  
Author(s):  
Stylianos Zikos ◽  
Maria Tsourma ◽  
Evdoxia E. Lithoxoidou ◽  
Anastasios Drosou ◽  
Dimosthenis Ioannidis ◽  
...  
Keyword(s):  
Knowledge Sharing ◽  
Knowledge Integration ◽  
Knowledge Exchange ◽  
User Acceptance ◽  
Work Environments ◽  
Manufacturing Industries ◽  
Rule Based ◽  
Industrial Work ◽  
Motivation And Engagement ◽  
Industrial Environments

This study evaluates user acceptance of a gamification-enabled collaboration and knowledge sharing platform that has been developed for use by personnel in industrial work environments, aiming at increasing motivation for knowledge exchange. The platform has been evaluated at two manufacturing industries by two groups of users, workers and supervisors, with regard to five criteria: usability, knowledge integration, working experience, user acceptance and overall impact. Results showed that even though the ratings from both industries were positive on all criteria, there is room for improvement on user acceptance and knowledge integration. Driven by this fact, a rule-based adaptive gamification approach which exploits information about workers is proposed in order to further increase motivation and engagement. Based on feedback received from the evaluation, guidelines related to functionalities and design of a gamified collaboration platform are provided. These guidelines can be followed when implementing collaboration tools with gamification support for industrial environments.

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