A Survey on TAXO Finder: An Efficient Taxonomy Learning Using Graph Based Approach - Kadam, Abhijeet Ashokrao; Swami, Shivputra Guruling (International Journal of Computer Sciences and Engineering, 2019)
Taxonomy learning knowledge is an essential project for knowledge acquisition, sharing, and classiﬁcation in addition to utility development and usage in diverse domains. To decrease human effort to build a taxonomy from scratch and enhance the quality of discovered taxonomy, we endorse a brand new taxonomy gaining knowledge of method, named taxo finder. Taxofinder takes 3 steps to mechanically build a taxonomy. First, it identiﬁes domain-speciﬁc standards from a website textual content corpus. 2nd, it builds a graph representing how such standards are related collectively primarily based on their co-occurrences. As the key approach in taxofinder, the taxonomy may be built manually however it`s far a complex manner when the information is so huge and it additionally produces some errors while taxonomy production. There may be diverse automated taxonomy creation techniques that are used to study taxonomy based totally on key-word terms, text corpus and from domain particular principles and so on. So it`s far required to construct taxonomy with less human effort and with much less error price. This paper affords certain records about those techniques.