A fast associative mining system based on search engine and concept graph for large-scale financial report texts

Kun Qian; Sachio Hirokawa; Kenji Ejima; Xiaoping Du

doi:10.1109/ICIFE.2010.5609447

A fast associative mining system based on search engine and concept graph for large-scale financial report texts

Kun Qian, Sachio Hirokawa, Kenji Ejima, Xiaoping Du

研究成果: 書籍/レポートタイプへの寄稿 › 会議への寄与

5 被引用数 (Scopus)

抄録

Association mining is widely used in pattern discovery. For large scale financial textual data analysis, however, association mining is relatively less applied due to low efficiency in text manipulation. This paper presents a fast finance textual mining system, based on search engine and concept graph, for large scale financial textual association mining and visualization. Through the experiments on ten years' financial reports of 6,049 companies from NASDAQ and NYSE from 1999 to 2008, it testified that this system could rapidly extracting the characteristic words among millions of texts and visualizing them by concept graph in seconds.

本文言語	英語
ホスト出版物のタイトル	Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010
ページ	675-679
ページ数	5
DOI	https://doi.org/10.1109/ICIFE.2010.5609447
出版ステータス	出版済み - 2010
イベント	2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010 - Chongqing, 中国継続期間: 9月 17 2010 → 9月 19 2010

出版物シリーズ

名前	Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010

その他

その他	2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010
国/地域	中国
City	Chongqing
Period	9/17/10 → 9/19/10

!!!All Science Journal Classification (ASJC) codes

会計
財務

文献へのアクセス

10.1109/ICIFE.2010.5609447

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引用スタイル

Qian, K., Hirokawa, S., Ejima, K., & Du, X. (2010). A fast associative mining system based on search engine and concept graph for large-scale financial report texts. In Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010 (pp. 675-679). Article 5609447 (Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010). https://doi.org/10.1109/ICIFE.2010.5609447

A fast associative mining system based on search engine and concept graph for large-scale financial report texts. / Qian, Kun; Hirokawa, Sachio; Ejima, Kenji その他.
Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010. 2010. p. 675-679 5609447 (Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010).

研究成果: 書籍/レポートタイプへの寄稿 › 会議への寄与

Qian, K, Hirokawa, S, Ejima, K & Du, X 2010, A fast associative mining system based on search engine and concept graph for large-scale financial report texts. in Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010., 5609447, Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010, pp. 675-679, 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010, Chongqing, 中国, 9/17/10. https://doi.org/10.1109/ICIFE.2010.5609447

Qian K, Hirokawa S, Ejima K, Du X. A fast associative mining system based on search engine and concept graph for large-scale financial report texts. In Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010. 2010. p. 675-679. 5609447. (Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010). doi: 10.1109/ICIFE.2010.5609447

Qian, Kun ; Hirokawa, Sachio ; Ejima, Kenji その他. / A fast associative mining system based on search engine and concept graph for large-scale financial report texts. Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010. 2010. pp. 675-679 (Proceedings - 2010 2nd IEEE International Conference on Information and Financial Engineering, ICIFE 2010).

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abstract = "Association mining is widely used in pattern discovery. For large scale financial textual data analysis, however, association mining is relatively less applied due to low efficiency in text manipulation. This paper presents a fast finance textual mining system, based on search engine and concept graph, for large scale financial textual association mining and visualization. Through the experiments on ten years' financial reports of 6,049 companies from NASDAQ and NYSE from 1999 to 2008, it testified that this system could rapidly extracting the characteristic words among millions of texts and visualizing them by concept graph in seconds.",

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A fast associative mining system based on search engine and concept graph for large-scale financial report texts

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出版物シリーズ

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