Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
An Examination of the Effect of the Contextual UI Design Quality of Mobile Shopping Applications on the Loyalty of Users to the Applications Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Text Classification Algorithm Based on SLAS-C

Authors : Zhichao Yin, Jun Xiang, Chunyong Yin, Jin Wang

Published in: Advances in Computer Science and Ubiquitous Computing

Publisher: Springer Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Nowadays, mobile marketing is becoming increasingly important both strategically and economically because of the mobile devices. Short text is becoming a popular text form which can be seen in many fields such as network news, QQ messages, comments in BBS and so forth. Besides, our mobile devices also contain a lot of data of short text. To extract useful information from the short text more efficiently, this paper proposes SLAS (semi-supervised learning method and SVM classifier) and CART (classification and regression tree) to improve the traditional methods, which can classify massive short texts to mining the useful information from the short texts. The experiment also shows a better result than before, which has a more than 10% increase, including precision rate, recall rate and F1 value, besides, the running time is reduced by half than the KNN algorithm.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter An Improved Trust Model Based on Time Effect
next chapter A Ground Segmentation Method Based on Gradient Fields for 3D Point Clouds
Literature
1.
Deng, N., Tian, Y.: New method in data mining—support vector machine (SVM), vol. 16, no. 2, pp. 113–126. Science Press (2004)
2.
Breiman, L., Friedman, J.H., Olshen, R.A., et al.: Classification and regression tree. Wadsworth Int. Group 37(15), 237–251 (1984)
3.
Cover, T.M., Hart, P.E.: Nearest neighbor pattern classification. IEEE Trans. Inf. Theor. 13(1), 21–27 (1967)CrossRef
4.
Yang, Y., Liu, X.: A re-examination of text categorization methods. In: Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 42–49 (1999)
5.
Fan, Y., Liu, H.: Research on Chinese short text classification based on Wikipedia. Mod. Libr. Inf. Technol. 24(3), 47–52 (2012)MathSciNet
6.
Banerjee, S., Ramanathan, K., Gupta, A.: Clustering short texts using Wikipedia. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 787–788 (2007)
7.
Lin, X., Zhang, M., Bao, X.: Short text classification method based on concept network. Comput. Eng. 36(21), 4–10 (2010)
8.
Li, X., Pang, J., et al.: Deep neural network for short-text sentiment classification. In: International Conference on Database Systems for Advanced Applications, pp. 168–175 (2016)
9.
Francisco, P., Julián-Iranzo, P., et al.: Classifying unlabeled short texts using a fuzzy declarative approach. Lang. Resour. Eval. 47(1), 151–178 (2013)CrossRef
Metadata
Title
Text Classification Algorithm Based on SLAS-C
Authors
Zhichao Yin
Jun Xiang
Chunyong Yin
Jin Wang
Copyright Year
2018
Publisher
Springer Singapore
Book
Advances in Computer Science and Ubiquitous Computing

Print ISBN: 978-981-10-7604-6

Electronic ISBN: 978-981-10-7605-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-7605-3_63