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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2008.12
- 수록면
- 1,749 - 1,757 (9page)
이용수
초록· 키워드
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This research proposes a modified version of single pass algorithm specialized for text clustering. Encoding documents into numerical vectors for using the traditional version of single pass algorithm causes the two main problems: huge dimensionality and sparse distribution. Therefore, in order to address the two problems, this research modifies the single pass algorithm into its version where documents are encoded into not numerical vectors but other forms. in the proposed version, documents are mapped into tables and the operation on two tables is defined for using the single pass algorithm. The goal of this research is to improve the performance of single pass algorithm for text clustering by modifying it into the specialized version.
목차
ABSTRACT
1. INTRODUCTION
2. PREVIOUS WORKS
3. DOCUMENT ENCODING
4. PROPOSED TEXT CLUSTERING SYSTEM
5. EMPIRICAL RESULTS
6. CONCLUSIONS
REFERENCES
참고문헌 (13)
참고문헌 신청
V. Hatzivassiloglou / 2000 / An Investigation of Linguistic Features and Clustering Algorithms for Topical Document Clustering / The Proceedings of 23rd SIGIR :224~231
G. Bote / 2002 / Document Organization using Kohonen’s Algorithm / Information Processing and Management 38(1):79~89
S. Kaski / 1998 / WEBSOM-Self Organizing Maps of Document Collections / Neurocomputing 21:101~117
T. Kohonen / 2000 / Self Organization of a Massive Document Collection / IEEE Transaction on Neural Networks 11(3):574~585
C. Ambroise / 1998 / Convergence of an EM-type algorithm for spatial clustering / Pattern Recognition Letters 19(10):919~927
G. Bote / 2002 / Document Organization using Kohonen’s Algorithm / Information Processing and Management 38(1):79~89
S. Kaski / 1998 / WEBSOM-Self Organizing Maps of Document Collections / Neurocomputing 21:101~117
T. Kohonen / 2000 / Self Organization of a Massive Document Collection / IEEE Transaction on Neural Networks 11(3):574~585
C. Ambroise / 1998 / Convergence of an EM-type algorithm for spatial clustering / Pattern Recognition Letters 19(10):919~927
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UCI(KEPA) : I410-ECN-0101-2012-004-004431888