Automatic taxonomy construction from textual documents - Luu, Anh Tuan (2017)
The explosion of unstructured text data makes it difficult to find information for our interests. To provide access to information effectively, it is important to organize the unstructured data in a structured and meaningful manner. Taxonomies, which serve as the backbone for structured knowledge, are useful for many NLP applications such as question answering and document clustering by organizing domain knowledge into a hierarchy of ‘is-a’ relations between terms. Currently, there have been an increasing number of public hand-crafted taxonomies available such as WordNet and Freebase. However, it will be more effective to use taxonomies that are created specifically for the domain of interest in practice rather than re-using existing taxonomies created for other tasks or domains. As such, we often face the challenge of creating a brand new taxonomy for a specific domain from scratch.