Abstract
Currently, various techniques for measuring the proximity between two objects in the internet network are continuously being developed. The objects in question are in the form of concepts, e-mails, words, and so on. Normalized Web Distance (NWD) has proven to be a simple, yet powerful measure of the semantic linkages between the two concepts. NWD has several approaches according to the object being measured, such as Normalized Google Distance (NGD) and Normalized Compression Distance (NCD). NGD and NCD have a way of determining similarity and calculating the distance to find the similarity of two different measuring objects. This paper shows and provides information on the performance of the two NWD approaches, namely NGD and NCD to facilitate understanding of the use of NGD and NCD on various problems. Correct understanding can put the NGD and the NCD in the right case.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
