A Collaborative Deep and Shallow Semisupervised Learning Framework for Mobile App Classification

Joint Authors

Chen, Tieming
Lv, MingQi
Huang, Chao
Wang, Ting

Source

Mobile Information Systems

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-02-14

Country of Publication

Egypt

No. of Pages

12

Main Subjects

Telecommunications Engineering

Abstract EN

With the rapid growth of mobile Apps, it is necessary to classify the mobile Apps into predefined categories.

However, there are two problems that make this task challenging.

First, the name of a mobile App is usually short and ambiguous to reflect its real semantic meaning.

Second, it is usually difficult to collect adequate labeled samples to train a good classifier when a customized taxonomy of mobile Apps is required.

For the first problem, we leverage Web knowledge to enrich the textual information of mobile Apps.

For the second problem, the mostly utilized approach is the semisupervised learning, which exploits unlabeled samples in a cotraining scheme.

However, how to enhance the diversity between base learners to maximize the power of the cotraining scheme is still an open problem.

Aiming at this problem, we exploit totally different machine learning paradigms (i.e., shallow learning and deep learning) to ensure a greater degree of diversity.

To this end, this paper proposes Co-DSL, a collaborative deep and shallow semisupervised learning framework, for mobile App classification using only a few labeled samples and a large number of unlabeled samples.

The experiment results demonstrate the effectiveness of Co-DSL, which could achieve over 85% classification accuracy by using only two labeled samples from each mobile App category.

American Psychological Association (APA)

Lv, MingQi& Huang, Chao& Chen, Tieming& Wang, Ting. 2020. A Collaborative Deep and Shallow Semisupervised Learning Framework for Mobile App Classification. Mobile Information Systems،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1192385

Modern Language Association (MLA)

Chen, Tieming…[et al.]. A Collaborative Deep and Shallow Semisupervised Learning Framework for Mobile App Classification. Mobile Information Systems No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1192385

American Medical Association (AMA)

Lv, MingQi& Huang, Chao& Chen, Tieming& Wang, Ting. A Collaborative Deep and Shallow Semisupervised Learning Framework for Mobile App Classification. Mobile Information Systems. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1192385

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1192385