Volume 7 Number 12 (Dec. 2012)
Home > Archive > 2012 > Volume 7 Number 12 (Dec. 2012) >
JSW 2012 Vol.7(12): 2787-2793 ISSN: 1796-217X
doi: 10.4304//jsw.7.12.2787-2793

A Novel Combine Forecasting Method for Predicting News Update Time

Mengmeng Wang1, 2, Xianglin Zuo1, Wanli Zuo1, 2 and Ying Wang1, 2
1College of Computer Science and Technology, Jilin University, Changchun, China
2Key Laboratory of Symbolic Computation and Knowledge Engineering attached to the Ministry of Education, Jilin

Abstract—With the rapid development of Internet, information provided by the Internet has shown explosive growth. In the face of massive and constantly updated information on the Internet, how the user can fast access to more valuable and more information has become one of the hot spots. The time of Web Page update appears to be erratic, so forecasting the update time of news reports is even more difficult. From the view of application, we can use mathematical models to maximize the approximation of variation, although it cannot be completely accurate. So is the predicting the update time of news which helps in improving the news crawler’s scheduling policy. In this paper, we proposed a combined predict algorithm for news update. In order to predict the update time of news, firstly, we applied the Exponential Smoothing method to our dataset, and we also have selected the optimal parameters. Secondly, we leveraged the Naive Bayes Model for prediction. Finally, we combined two methods for Combination Forecasting, as well as made a compare with former methods. Through the experiments on Sohu News, we show that Combination Forecasting method outperforms other methods while estimating localized rate of updates.

Index Terms—Exponential Smoothing Method, Naive Bayes Model, Combination Forecasting, News Update Time


Cite: Mengmeng Wang, Xianglin Zuo, Wanli Zuo and Ying Wang, "A Novel Combine Forecasting Method for Predicting News Update Time," Journal of Software vol. 7, no. 12, pp. 2787-2793, 2012.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
  • Apr 26, 2021 News!

    Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec)     [Click]

  • Jun 22, 2020 News!

    Papers published in JSW Vol 14, No 1- Vol 15 No 4 have been indexed by DBLP     [Click]

  • Sep 13, 2021 News!

    The papers published in Vol 16, No 6 have all received dois from Crossref    [Click]

  • Jan 28, 2021 News!

    [CFP] 2021 the annual meeting of JSW Editorial Board, ICCSM 2021, will be held in Rome, Italy, July 21-23, 2021   [Click]

  • Sep 13, 2021 News!

    Vol 16, No 6 has been published with online version     [Click]