Mr. Libin Hou Profile

Libin Hou

at Krirk Univ

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 20 October 2022 Paper

Interior design data analysis based on collaborative filtering algorithm model

Libin Hou, Donghui Cui

Proceedings Volume 12350, 1235027 (2022) https://doi.org/10.1117/12.2653190

KEYWORDS: Feature extraction, Data modeling, Data analysis, Model-based design, Computer simulations, Linear filtering, Filtering (signal processing), Statistical analysis, Operating systems, Mobile devices

Read Abstract +

In order to shorten the time of interior design recommendation and quickly recommend interested interior design to users, an interior design data analysis technology based on collaborative filtering algorithm model is proposed. By analyzing the word segmentation of interior design, the weight distribution of collaborative filtering of interior design is analyzed. Carry out keyword feature selection and data analysis for interior design content. When the similar keywords in the data analysis are more than 35%, the interior design feature extraction based on collaborative filtering model will be completed. According to the initial score of the user's interior design, calculate the weight of the interior design, predict the final score of the user's interior design through the weight vector value, use the interior design data analysis to determine the implementation steps of the recommendation algorithm, and complete the design of the interior design recommendation algorithm model. Finally, through the interior design collaborative filtering recommendation model, we can achieve 100% interior design recommendation. The experimental results show that compared with the traditional recommendation technology, the indoor design recommendation time based on collaborative filtering algorithm is reduced by 80%.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years