Online geovisualization with fast kernel density estimator

Hajime Hotta, Masafumi Hagiwara

研究成果: Conference contribution

5 引用 (Scopus)

抄録

Visualization of geographic log-data is one of the key issues on geovisualization, which is defined as a research field of visualizing geographic information. This paper aims to visualize them interactively using graphics like thermograph, mashuped with interactive mapping system (IMS), such as Google Map. While conventional researches employ probability density function estimation algorithms, the problems are twofold. One is that the focused data should be analyzed rapidly online during the interaction between systems and users, for the map size and location can be changed flexibly with IMS. The other is that focused data may be sparse when the map is zoomed in. In general, EM algorithm, a commonly-used probabilistic density approximator, is not robust to sparseness and it takes long time for model construction. Parzen window is also a simple, well-known technique but it requires many kernels that make calculation costs high. The proposed method is a novel, simple kernel density estimator which is fast for model construction with high robustness to sparse data. The proposed method is based on Parzen window and employs a clustering algorithm inspired by fuzzy ART (Adaptive Resonance Theory) to reduce kernels. From the experimental results, estimation accuracy excels the conventional methods with various benchmarking models.

元の言語English
ホスト出版物のタイトルProceedings - 2009 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2009
ページ622-625
ページ数4
1
DOI
出版物ステータスPublished - 2009
イベント2009 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2009 - Milano, Italy
継続期間: 2009 9 152009 9 18

Other

Other2009 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2009
Italy
Milano
期間09/9/1509/9/18

Fingerprint

Benchmarking
Clustering algorithms
Probability density function
Visualization
Costs

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications

これを引用

Hotta, H., & Hagiwara, M. (2009). Online geovisualization with fast kernel density estimator. : Proceedings - 2009 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2009 (巻 1, pp. 622-625). [5284907] https://doi.org/10.1109/WI-IAT.2009.105

Online geovisualization with fast kernel density estimator. / Hotta, Hajime; Hagiwara, Masafumi.

Proceedings - 2009 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2009. 巻 1 2009. p. 622-625 5284907.

研究成果: Conference contribution

Hotta, H & Hagiwara, M 2009, Online geovisualization with fast kernel density estimator. : Proceedings - 2009 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2009. 巻. 1, 5284907, pp. 622-625, 2009 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2009, Milano, Italy, 09/9/15. https://doi.org/10.1109/WI-IAT.2009.105
Hotta H, Hagiwara M. Online geovisualization with fast kernel density estimator. : Proceedings - 2009 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2009. 巻 1. 2009. p. 622-625. 5284907 https://doi.org/10.1109/WI-IAT.2009.105
Hotta, Hajime ; Hagiwara, Masafumi. / Online geovisualization with fast kernel density estimator. Proceedings - 2009 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2009. 巻 1 2009. pp. 622-625
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