Author : Tarak hussain, p. s aithal,
Keyword : Lsh, dataset, clustering, fake name
Subject : Management
Article Type : Original article (research)
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Abstract : This paper proposes a method for generating fake names using Locality Sensitive Hashing (LSH). The approach involves creating a hash function that maps real names to fake names based on phonetic similarity measures. The Data set is taken from Kaggle which is reengineered. The LSH algorithm is then used to find pairs of real and fake names that have similar phonetic codes. The proposed method is implemented in Python using the data sketch library, and a sample code is provided to demonstrate its feasibility. The results show that LSH can be used to generate fake names that are similar in structure and characteristics to real names, and the approach could potentially be useful in contexts where anonymity is desired. However, the ethical and legal implications of using fake names should be carefully considered before adopting this approach.
Article by : Sreeramana Aithal
Article add date : 2023-03-31
How to cite : Tarak hussain, p. s aithal,. (2023-March-31). Fake name clustering using locality sensitive hashing. international journal of enhanced research in management & computer applications, 12(3), 1-5. issn: 2319-7471,. retrieved from https://www.openacessjournal.com/abstract/1231