Sequential clustering and condensing the meaning of texts into centroid terms

Name: Maytiyanin Komkhao

Organization : Rajamangala University of Technology Phra Nakhon. Faculty of Science and Technology

Name: Kubek, Mario

Organization : Fernuniversitat in Hagen. Faculty of Mathematics and Computer Science

Name: Halang, Wolfgang A.

Organization : Qingdao University of Science and Technology.

keyword: Centroid Distance Measure

; Sequential Clustering

; Text Analysis

; Centroid terms

LCSH: CLUSTER ANALYSIS

LCSH: DOCUMENT CLUSTERING

Abstract: When run, most traditional clustering algorithms require the number of clusters sought to be specied beforehand, and all clustered items to be present. These two, for practical applications very serious shortcomings are overcome by a straightforward sequential clustering algorithm. Its most crucial constituent is a distance measure whose suitable choice is discussed. It is shown how sequentially obtained cluster sets can be improved by reclustering, and how items considered as outliers can be removed. As a case study, the feasibility of applying the method and a centroid-based distance measure to nd and group semantically similar documents in text analysis is investigated."

King Mongkut's University of Technology North Bangkok. Central Library

Address: Bangkok

Email: library@kmutnb.ac.th

Created: 2561

Modified: 2024-09-03

Issued: 2018-07-24

บทความ/Article

application/pdf

BibliograpyCitation : วารสารเทคโนโลยีสารสนเทศ. ปีที่ 14, ฉบับที่ 1 ‪‪(ม.ค.-มิ.ย. 61)‬‬, หน้า 1-10

eng

©copyrights King Mongkut's University of Technology North Bangkok

ลำดับที่.	ชื่อแฟ้มข้อมูล	ขนาดแฟ้มข้อมูล	จำนวนเข้าถึง	วัน-เวลาเข้าถึงล่าสุด
1	ch27_01.pdf	771.4 KB

ใช้เวลา

0.032446 วินาที