Critical review of web mining for learning ontologies
Dr. Rana Ajay*, Mr. Kumar Anuj**
*Shobhit Institute of Engineering and Technology (Deemed to be University), Meerut, Uttar Pradesh, India, Email id: email@example.com
**School of Computer Science and Engineering, Faculty of Engineering and Technology, Shobhit Institute of Engineering and Technology (Deemed to be University), Meerut, Uttar Pradesh, India, Email id: firstname.lastname@example.org
Online Published on 03 January, 2022.
The purpose of this paper is to study and discuss the topic of creating ontologies using Semantic Web Mining, which is described as a mix of the two rapidly expanding research fields of Semantic Web and Web Mining. The Semantic Web is the second-generation WWW, supplemented by machine-processable information that assists the user in his duties. Web mining is the application of data mining techniques to the content, structure, and usage of Web resources.This can aid in the discovery of global and local structural "models" or "patterns" within and across Web pages, as well as the extraction of ontologies. The automatic or semi-automated development of ontologies, which includes extracting the related domain's words and connections between such concepts, and encoding them using an ontology language for simple retrieval. Because manually creating ontologies is very time-consuming and labor-intensive, there is a strong need to automate the process. This paper provides an outline of where the two fields now intersect, as well as suggestions for how a tighter integration may be beneficial.
Knowledge Discovery, Ontology, Ontology Learning, Semantic Web, Web Mining.