Hot Topic Clustering Based On Words Distances

DOI

10.2991/fmsmt-17.2017.116How to use a DOI?

Keywords

Clustering, Words distances

Abstract

In order to find the relevance of the key words in the hot topics effectively, we proposed a clustering method based on words-distances. We calculated the distances between the words firstly, then calculated the sectional density of each words. We regarded the words which have higher sectional density and far away from sectional density point as the center point in the clustering. After find the center point, we start to clustering. This method through decision diagram on estimating the number of clusters. At last, we can find the results on the evaluating indicator of accuracy rate and recall rate.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Hongtao Liu
AU  - Hongwei Guan
AU  - Jie Jian
AU  - Xueyan Liu
PY  - 2017/04
DA  - 2017/04
TI  - Hot Topic Clustering Based On Words Distances
BT  - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
PB  - Atlantis Press
SP  - 573
EP  - 577
SN  - 2352-5401
UR  - https://doi.org/10.2991/fmsmt-17.2017.116
DO  - 10.2991/fmsmt-17.2017.116
ID  - Liu2017/04
ER  -