Bicluster-Network Method and Its Application to Movie Recommendation

2014 ◽  
pp. 147-153 ◽  
Author(s):  
Tatsuya Saito ◽  
Yoshifumi Okada
Keyword(s):  
Network Method ◽  
Movie Recommendation

NETWORK METHOD OF EVOLUTION SYNTHESIS OF BEHAVIOR TESTS

2017 ◽  
Vol 25 (101) ◽  
pp. 452-457
Author(s):  
Alexander N., Martynyuk ◽  
◽  
Dmitry Oleksandrovich, Martynyuk ◽  
Anna S., Sugak
Keyword(s):  
Network Method

Shunt Control on Smart Structures Using Genetic Algorithm and Neural Network Method.

2019 ◽  
Author(s):  
Venicio Silva Araujo ◽  
Guilherme Silva Prado ◽  
Heinsten Frederich Leal dos Santos
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Smart Structures ◽  
Neural Network Method ◽  
Network Method ◽  
Shunt Control

A FIRST APPROACH TO MODELLING A STEAM GENERATOR BASED ON HEAT EXCHANGERS NETWORK METHOD

2019 ◽  
Author(s):  
Augusto Delavald Marques ◽  
Caroline Mével ◽  
Paulo Smith Schneider ◽  
Jéssica Duarte ◽  
Guilherme Barth Rossi
Keyword(s):  
Steam Generator ◽  
Heat Exchangers ◽  
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.

Methods for evaluation the manufacturability of a vehicle

2020 ◽  
pp. 152-160
Keyword(s):  
Neural Network ◽  
Initial Data ◽  
Comparative Data ◽  
Training Algorithm ◽  
Neural Network Method ◽  
The Neural Network ◽  
Network Method ◽  
Calculation Results ◽  
Production And Operation

Methods for evaluation the manufacturability of a vehicle in the field of production and operation based on an energy indicator, expert estimates and usage of a neural network are stated. By using the neural network method the manufacturability of a car in a complex and for individual units is considered. The preparation of the initial data at usage a neural network for predicting the manufacturability of a vehicle is shown; the training algorithm and the architecture for calculating the manufacturability of the main units are given. According to the calculation results, comparative data on the manufacturability vehicles of various brands are given.

scholarly journals Movie Recommendation through Multiple Bias Analysis

2021 ◽  
Vol 11 (6) ◽  
pp. 2817
Author(s):  
Tae-Gyu Hwang ◽  
Sung Kwon Kim
Keyword(s):  
Decision Making ◽  
Recommender System ◽  
Real World ◽  
Matrix Factorization ◽  
User Preferences ◽  
Improve Performance ◽  
Bias Analysis ◽  
Useful Knowledge ◽  
Existing Problems ◽  
Movie Recommendation

A recommender system (RS) refers to an agent that recommends items that are suitable for users, and it is implemented through collaborative filtering (CF). CF has a limitation in improving the accuracy of recommendations based on matrix factorization (MF). Therefore, a new method is required for analyzing preference patterns, which could not be derived by existing studies. This study aimed at solving the existing problems through bias analysis. By analyzing users’ and items’ biases of user preferences, the bias-based predictor (BBP) was developed and shown to outperform memory-based CF. In this paper, in order to enhance BBP, multiple bias analysis (MBA) was proposed to efficiently reflect the decision-making in real world. The experimental results using movie data revealed that MBA enhanced BBP accuracy, and that the hybrid models outperformed MF and SVD++. Based on this result, MBA is expected to improve performance when used as a system in related studies and provide useful knowledge in any areas that need features that can represent users.

scholarly journals The approximation neural-network method for solving nonlinear multi-criteria inverse problems of geophysics

2021 ◽  
Vol 1715 ◽  
pp. 012045
Author(s):  
M I Shimelevich ◽  
E A Obornev ◽  
I E Obornev ◽  
E A Rodionov
Keyword(s):  
Neural Network ◽  
Inverse Problems ◽  
Neural Network Method ◽  
Network Method

Genre based hybrid filtering for movie recommendation engine

2021 ◽  
Author(s):  
Arighna Roy ◽  
Simone A. Ludwig
Keyword(s):  
Hybrid Filtering ◽  
Movie Recommendation
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