Constructing Gene Networks by Using a New Bayesian Network Method

2009 ◽  
Author(s):  
Zhihua Du ◽  
Yiwei Wang ◽  
Zhen Ji ◽  
Q. H. Wu
Keyword(s):  
Bayesian Network ◽  
Gene Networks ◽  
Network Method

A Resamping Approach for Customer Gender Prediction Based on E-Commerce Data

2017 ◽  
Vol 3 (1) ◽  
pp. 76 ◽  
Author(s):  
Duong Tran Duc ◽  
Pham Bao Son ◽  
Tan Hanh ◽  
Le Truong Thien
Keyword(s):  
Data Mining ◽  
Bayesian Network ◽  
Web Applications ◽  
Service Providers ◽  
Main Idea ◽  
Classification Methods ◽  
Cost Sensitive Learning ◽  
Network Method ◽  
Demographic Attributes ◽  
Privacy Issues

Demographic attributes of customers such as gender, age, etc. provide the important information for e-commerce service providers in marketing, personalization of web applications. However, the online customers often do not provide this kind of information due to the privacy issues and other reasons. In this paper, we proposed a method for predicting the gender of customers based on their catalog viewing data on e-commerce systems, such as the date and time of access, the products viewed, etc. The main idea is that we extract the features from catalog viewing information and employ the classification methods to predict the gender of the viewers. The experiments were conducted on the datasets provided by the PAKDD’15 Data Mining Competition and obtained the promising results with a simple feature design, especially with the Bayesian Network method along with other supporting techniques such as resampling, cost-sensitive learning, boosting etc.

scholarly journals An improved Bayesian network method for fault diagnosis

2018 ◽  
Vol 51 (21) ◽  
pp. 341-346 ◽  
Author(s):  
Yalin Wang ◽  
Haibing Yang ◽  
Xiaofeng Yuan ◽  
Yue Cao
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Network Method

scholarly journals Bayesian network method for decision-making about the social sustainability of infrastructure projects

2018 ◽  
Vol 176 ◽  
pp. 521-534 ◽  
Author(s):  
Leonardo A. Sierra ◽  
Víctor Yepes ◽  
Tatiana García-Segura ◽  
Eugenio Pellicer
Keyword(s):  
Decision Making ◽  
Bayesian Network ◽  
Social Sustainability ◽  
Infrastructure Projects ◽  
The Social ◽  
Network Method

Investigation of the Impact of BIM&IPD on Change Orders Using Bayesian Network Method

2013 ◽  
Vol 397-400 ◽  
pp. 2064-2068 ◽  
Author(s):  
Mei Liu
Keyword(s):  
Bayesian Network ◽  
Construction Projects ◽  
Negative Impact ◽  
Information Modeling ◽  
Professional Relationships ◽  
Good Tool ◽  
Change Orders ◽  
Network Method ◽  
Building Information ◽  
The Impact

Change orders present one of the largest sources of cost growth on building construction projects and have negative impact on productivity, labor efficiency and building environment. Building Information Modeling (BIM) is proved a high technology that greatly benefits both design and construction, greatly promoting the design visualization and construction 4-D modeling. Driven by BIM, Integrated Project Delivery (IPD) emphasizes communication in the collaborative process by avoiding adversarial or counter-productive professional relationships to reduce waste and rework. If BIM&IPD can be properly applied in project, quite a lot change orders can be avoided and then project cost will be reduced. This paper investigates the impact of BIM&IPD on construction change orders using Bayesian Network method. Bayesian Network is a graphic model representing cause and effect relationship between change orders and BIM&IPD. In this paper, evidence reasoning and probabilistic inference analyses are conducted to indicate the causes in light of the results and forecast the results according to causes. From the analysis, Bayesian Network is proved a good tool for construction managers to make decisions.

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