The Micro-Video Label Classification System Design Based on Network Data Acquisition

Bin Zhang; Jia Lun Song; Zheng Zheng Liu; Hai Ji

doi:10.4028/www.scientific.net/AMM.738-739.556

Paper Titles

A Novel Fast Pedestrian Detection Method
p.538

An Image Classification Algorithm Based on SVM
p.542

A Character Recognizer Based on BP Network
p.546

A Study of a Normalized Error Calibration Method Based on Parallel High-Speed Data Acquisition System
p.551

The Micro-Video Label Classification System Design Based on Network Data Acquisition
p.556

Boundary Stitching Method for Block-Based Parallel Error Diffusion
p.560

Research on the Method of Screening the Real Vehicle Data Fragment for Driving Cycle
p.564

Application of Statistical Methods in Experimental Modal Frequency Extraction
p.569

A Novel Image Inpainting Method Based on Sparse Decomposition
p.573

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 738-739The Micro-Video Label Classification System Design...

The Micro-Video Label Classification System Design Based on Network Data Acquisition

Abstract:

Micro-video label classification system (MLCS) is designed to tag and classify micro-videos by a specific set of labels, which are extracted from users’ comments on the internet. These labels not only describe the micro-video’s features in various aspects, but also deliver the audiences’ attitudes and concern. Combining the high-ranking labels can effectively organize the creative elements to help producing new video scripts and categories. It breaks the traditional limit of linear producing process and makes the micro-videos’ story more topical and integrate.

You might also be interested in these eBooks

Sensors, Measurement, Intelligent Materials and Technologies III

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 738-739)

Pages:

556-559

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.738-739.556

Citation:

Cite this paper

Online since:

March 2015

Authors:

Bin Zhang*, Jia Lun Song, Zheng Zheng Liu, Hai Ji

Keywords:

Inverse Document Frequency (IDF), Micro-Video Label Classification System (MLCS), Text Analysis

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] S.Z. Zhao F. Wang and R. Yang: Analysis of the current situation of global network video business development. MSTT Vol. 3 (2011), pp.6-9.

Google Scholar

[2] Alexis C. Madrigal: How Netflix Reverse Engineered Hollywood (The Atlantic, USA 2014).

Google Scholar

[3] Tu Fang: Differences of micro-labels between Baidu Video and Netflix (PingWest, 2014). In Chinese.

Google Scholar

[4] X. Luo D.L. Xia and P.L. Yan: Improved feature selection method and TF-IDF formula based on word frequency differentia. Computer Applications Vol. 25 (2005), p.2031-(2033).

Google Scholar