TY  - JOUR
T1  - Automatic Construction of Reduced Dimensional Cluster-based Keyword Association Networks using LSI
AU  - Yoo, Han-mook 
AU  - Kim, Han-joon 
AU  - Chang, Jae-young 
JO  - Journal of KIISE, JOK
PY  - 2017
DA  - 2017/1/14
DO  - 10.5626/JOK.2017.44.11.1236
KW  - latent semantic indexing
KW  - mutual information
KW  - maximal spanning tree
KW  - clustering
KW  - keyword extraction
KW  - text mining
AB  - In this paper, we propose a novel way of producing keyword networks, named LSI-based ClusterTextRank, which extracts significant key words from a set of clusters with a mutual information metric, and constructs an association network using latent semantic indexing (LSI). The proposed method reduces the dimension of documents through LSI, decomposes documents into multiple clusters through k-means clustering, and expresses the words within each cluster as a maximal spanning tree graph. The significant key words are identified by evaluating their mutual information within clusters. Then, the method calculates the similarities between the extracted key words using the term-concept matrix, and the results are represented as a keyword association network. To evaluate the performance of the proposed method, we used travel-related blog data and showed that the proposed method outperforms the existing TextRank algorithm by about 14% in terms of accuracy.