An Analysis of the Features Considerable for NFT Recommendations

Piyadigama, Dinuka; Poravi, Guhanathan

dc.contributor.author	Piyadigama, Dinuka
dc.contributor.author	Poravi, Guhanathan
dc.date.accessioned	2025-04-12T13:22:35Z
dc.date.available	2025-04-12T13:22:35Z
dc.date.issued	2022
dc.identifier.citation	Piyadigama, D. and Poravi, G. (2022) ‘An Analysis of the Features Considerable for NFT Recommendations’, in 2022 15th International Conference on Human System Interaction (HSI). 2022 15th International Conference on Human System Interaction (HSI), pp. 1–7. Available at: https://doi.org/10.1109/HSI55341.2022.9869497.	en_US
dc.identifier.uri	https://ieeexplore.ieee.org/document/9869497
dc.identifier.uri	http://dlib.iit.ac.lk/xmlui/handle/123456789/2242
dc.description.abstract	This research explores the methods that Non-fungible Token (NFT)s can be recommended to people who inter-act with NFT-marketplaces to explore NFTs of preference and similarity to what they have been searching for. While exploring past methods that can be adopted for recommendations, the use of NFT traits for recommendations has been explored. The outcome of the research highlights the necessity of using multiple Recommender Systems to present the user with the best possible NFTs when interacting with decentralized systems.	en_US
dc.language.iso	en	en_US
dc.publisher	IEEE	en_US
dc.subject	Non-fungible Tokens	en_US
dc.subject	Recommender Systems	en_US
dc.subject	Data mining	en_US
dc.title	An Analysis of the Features Considerable for NFT Recommendations	en_US
dc.type	Article	en_US