Data Mining and Nonlinear Non-stationary Processes Forecasting by Using Linguistic Modeling Method

2019 ◽  
pp. 409-418
Author(s):  
Tatiana Shulkevich ◽  
Yurii Selin ◽  
Vilen Savchenko
Keyword(s):  
Data Mining ◽  
Modeling Method ◽  
Stationary Processes ◽  
Linguistic Modeling

Research on Persona-Based User Requirement in the Future Exploratory Products Design

2014 ◽  
Vol 912-914 ◽  
pp. 1710-1713
Author(s):  
Qing Zhang ◽  
Sui Huai Yu ◽  
Ming Jiu Yu
Keyword(s):  
Data Mining ◽  
User Modeling ◽  
Modeling Method ◽  
Mobile Internet ◽  
User Requirement ◽  
Operating Rules ◽  
The Future ◽  
Key Factor

During the design processing of the future exploratory products, requirements from users seems to be a key factor for products availability achievement. As a practical user modeling method, Persona may accomplish the potential needs data mining effectively based on the analyzing of users. This review mainly focused on how to apply the persona in the exploratory products investigation to acquire useful information from the products design. The method to establish persona and the operating rules were also discussed in this article. The concept of the mobile internet device in future was used as an case to demonstrate the persona mentioned above.

scholarly journals A Sentiment Delivering Estimate Scheme Based on Trust Chain in Mobile Social Network

2015 ◽  
Vol 2015 ◽  
pp. 1-20 ◽  
Author(s):  
Meizi Li ◽  
Yang Xiang ◽  
Bo Zhang ◽  
Zhenhua Huang
Keyword(s):  
Data Mining ◽  
Social Network ◽  
Sentiment Analysis ◽  
Significant Role ◽  
Evaluation Method ◽  
Modeling Method ◽  
Chain Model ◽  
Mobile Social Network ◽  
Trust Chain ◽  
Network Platform

User sentiment analysis has become a flourishing frontier in data mining mobile social network platform since the mobile social network plays a significant role in users’ daily communication and sentiment interaction. This study studies the scheme of sentiment estimate by using the users’ trustworthy relationships for evaluating sentiment delivering. First, we address an overview of sentiment delivering estimate scheme and propose its related definitions, that is, trust chain among users, sentiment semantics, and sentiment ontology. Second, this study proposes the trust chain model and its evaluation method, which is composed of evaluation of atomic, serial, parallel, and combined trust chains. Then, we propose sentiment modeling method by presenting its modeling rules. Further, we propose the sentiment delivering estimate scheme from two aspects: explicit and implicit sentiment delivering estimate schemes, based on trust chain and sentiment modeling method. Finally, examinations and results are given to further explain effectiveness and feasibility of our scheme.

scholarly journals RESEARCH OF FUZHOU HISTORICAL BUILDING MANAGEMENT PLATFORM BASED ON DATA WAREHOUSE TECHNOLOGY

2019 ◽  
Vol XLII-2/W15 ◽  
pp. 671-674
Author(s):  
W. B. Li ◽  
G. L. Li ◽  
Y. Yang
Keyword(s):  
Data Mining ◽  
Data Warehouse ◽  
Modeling Method ◽  
Historic Buildings ◽  
Historical Buildings ◽  
Historical Building ◽  
Management Platform ◽  
Data Support ◽  
Management Indicators ◽  
Building Management

<p><strong>Abstract.</strong> In order to solve the problem of "data island" in the management of Fuzhou historical buildings. This paper analyzes historical building management needs and historical building management indicators. Then the data warehouse model of historic buildings is constructed by using dimension modeling method, and a set of data warehouse of Fuzhou historic buildings is designed and established. Finally, a historical building management platform was built on the basis of the historical building data warehouse, which realized the entry, standardization, extraction and cleaning of historical building management data. It provides data support for data mining of historic buildings in order to realize the protection, activation, utilization and standardized management of Fuzhou historic buildings.</p>

Fuzzy modeling method based on data mining

2008 ◽  
Author(s):  
Yongfu Wang ◽  
Hong Zhao ◽  
Jiren Liu ◽  
Tianyou Chai
Keyword(s):  
Data Mining ◽  
Fuzzy Modeling ◽  
Modeling Method

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining
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