Paper Info
Title
Feature Extraction Algorithm and Optimization for Mass TV Audience
Abstract
User viewing feature can be extracted from TV user's channel viewing data for improving the targeted TV advertising. In this paper, we propose a basic viewing feature extraction algorithm in small sample environment to prove the algorithm logic and check the analysis process quickly. However if the viewing behavior data come from mass TV audience, it requires higher speed feature extraction algorithm. Therefore, we have optimized our algorithm based on four methods including data reading mode, data type, data table structure and data structure. After optimizations, the data processing efficiency rise 67 times.
Year
DOI
Venue
2015
10.1109/CyberC.2015.35
CyberC
Keywords
Field
DocType
Feature extraction, Algorithm optimization, Mass data, Data preprocessing, Python
Data structure,Data mining,Data processing,Algorithm design,Computer science,Communication channel,Data pre-processing,Feature extraction,Data type,Python (programming language)
Conference
Citations 
PageRank 
References 
0
0.34
3
Authors
3
Name
Order
Citations
PageRank
Fan Zhang109.13
Zheng Chen25019256.89
Jinyao Yan3103.62