Prediction of search data volume based on time-series clustering and ARMA models

Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science)

Volumn 39, Issue 4, 2011, Pages 21-25

  Sun, Cheng Jie ^a   Liu, Feng ^a   Lin, Lei ^a   Liu, Bing Quan ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

ARMA model; Dynamic time warping distance; K medoid algorithm; Search data volume; Time series

Indexed keywords

ARMA MODEL; AUTOREGRESSIVE MOVING AVERAGE MODEL; BUSINESS STRATEGY; CLUSTER CENTERS; CLUSTERING RESULTS; DATA PREPROCESSING; DATA VOLUME; K-MEDOID ALGORITHMS; SEARCH TERMS; SEARCH VOLUME; SIMILARITY ANALYSIS; TIME SERIES PREDICTION;

CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; FORECASTING; PLANNING; PRODUCT DEVELOPMENT; TIME SERIES;

TIME SERIES ANALYSIS;

EID: 79959690431     PISSN: 1000565X     EISSN: None     Source Type: Journal    
DOI: 10.3969/j.issn.1000-565X.2011.04.004     Document Type: Article

References (12)

1. Weigend A S, Gershenfeld N A. Time series prediction: forecasting the future and understanding the past [C]//Proc of the NATO Advanced Research Workshop on Comparative Time Series Analysis. MA: Addison-Wesley, 1994.
2. Taken S F. Detecting strange attractors in turbulence [J]. Lecture Notes in Mathematics, 1981, 898(2): 366-381.
3. Maguire L P, Roche B, Mcginnity T M. Predicting a chaotic time series using a fuzzy neural network [J]. Information Sciences, 1998, 112(1/2/3/4): 125-136.
4. 2002: 106-132.
5. 2000.
6. Kaufman L, Rousseeuw P J. Clustering by means of medoids [C]//Proc of Statistical Data Analysis Based on the L1-Norm and Related Methods. Amsterdam: North-Holland, 1987: 405-416.
7. Davies D L, Bouldin D W. A cluster separation measure [J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 1979, 1(4): 224-227.
8. Berndt D J, Clifford J. Using dynamic time warp to find patterns in time series [C]//Proc of AAAI-94 Workshop on Knowledge Discovery in Database. Washington: AAAI Press, 1994: 359-370.
9. Keogh E J, Pazzani M J. Derivative dynamic time warping [C]//Proc of the First SIAM International Conference on Data Mining. Chicago: SDM, 2001.
10. Das G, Lin K I, Mannila H. Rule discovery from time series [C]// Proc of the 3rd International Conference of Knowledge Discovery and Data Mining. New York: ACM SIGKDD, 1998: 16-22.
11. Dimitriadou E, Dolnicar S, Weingessel A. An examination of indexes for determining the number of cluster in binary data sets [J]. Psychomctrika, 2002, 67(1): 137-160.
12. Armstrong J S, Collopy F. Error measures for generalizing about forecasting methods: empirical comparisons [J]. International Journal of Forecasting, 1992, 8(1): 69-80.