Incremental hierarchical text clustering methods: a review
Fernando Simeone Maik Olher Chaves Ahmed Esmin
The growth in Internet usage has contributed to a large volume of
continuously available data, and has created the need for automatic and
efficient organization of the data. In this context, text clustering techniques
are significant because they aim to organize documents according to their
characteristics. More specifically, hierarchical and incremental clustering
techniques can organize dynamic data in a hierarchical form, thus guaranteeing
that this organization is updated and its exploration is facilitated. Based on
the relevance and contemporary nature of the field, this study aims to analyze
various hierarchical and incremental clustering techniques; the main
contribution of this research is the organization and comparison of the
techniques used by studies published between 2010 and 2018 that aimed to texts
documents clustering. We describe the principal concepts related to the
challenge and the different characteristics of these published works in order
to provide a better understanding of the research in this field.