Despite significant successes achieved in knowledge discovery, traditional machine
learning methods may fail to obtain satisfactory performances when dealing with complex …

Document clustering is automatic organization of documents into clusters so that documents
within a cluster have high similarity in comparison to documents in other clusters. It has been …

With the development of high-throughput technology and the accumulation of biomedical
data, the prior information of biological entity can be calculated from different aspects …

Abstract Motivation: Medical Subject Headings (MeSH) indexing, which is to assign a set of
MeSH main headings to citations, is crucial for many important tasks in biomedical text …

MEDLINE is the largest biomedical literature database. It is updated daily with 200–4,000
citations. This permanent growth induces the need of a good MEDLINE abstract clustering to …

Motivation With the rapid increase of biomedical articles, large-scale automatic Medical
Subject Headings (MeSH) indexing has become increasingly important. FullMeSH, the only …

Abstract Motivation: Medical Subject Headings (MeSHs) are used by National Library of
Medicine (NLM) to index almost all citations in MEDLINE, which greatly facilitates the …

Text clustering is considered one of the most important topics in modern data mining.
Nevertheless, text data require tokenization which usually yields a very large and highly …

The objective of cluster structure ensemble is to find a unified cluster structure from multiple
cluster structures obtained from different datasets. Unfortunately, not all the cluster structures …

As an effective method for clustering applications, the clustering ensemble algorithm
integrates different clustering solutions into a final one, thus improving the clustering …