Title
Clustering short text and its evaluation
Abstract
Recently there has been an increase in interest towards clustering short text because it could be used in many NLP applications. According to the application, a variety of short text could be defined mainly in terms of their length (e.g. sentence, paragraphs) and type (e.g. scientific papers, newspapers). Finding a clustering method that is able to cluster short text in general is difficult. In this paper, we cluster 4 different corpora with different types of text with varying length and evaluate them against the gold standard. Based on these clustering experiments, we show how different similarity measures, clustering algorithms, and cluster evaluation methods effect the resulting clusters. We discuss four existing corpus based similarity methods, Cosine similarity, Latent Semantic Analysis, Short text Vector Space Model, and Kullback-Leibler distance, four well known clustering methods, Complete Link, Single Link, Average Link hierarchical clustering and Spectral clustering, and three evaluation methods, clustering F-measure, adjusted Rand Index, and V. Our experiments show that corpus based similarity measures do not significantly affect the clusters and that the performance of spectral clustering is better than hierarchical clustering. We also show that the values given by the evaluation methods do not always represent the usability of the clusters.
Year
DOI
Venue
2012
10.1007/978-3-642-28601-8_15
CICLing (2)
Keywords
Field
DocType
clustering f-measure,short text,evaluation method,clustering experiment,spectral clustering,hierarchical clustering,clustering method,average link hierarchical clustering,clustering algorithm,cluster evaluation methods effect
k-medians clustering,Hierarchical clustering,Fuzzy clustering,Data mining,Clustering high-dimensional data,Correlation clustering,Pattern recognition,Computer science,Artificial intelligence,Brown clustering,Cluster analysis,Single-linkage clustering
Conference
Citations 
PageRank 
References 
6
0.43
11
Authors
3
Name
Order
Citations
PageRank
Prajol Shrestha170.80
Christine Jacquin2568.53
Béatrice Daille330634.40