A Unified Framework for Providing Recommendations in Social Tagging Systems Based on Ternary Semantic Analysis

—Social Tagging is the process by which many users add metadata in the form of keywords, to annotate and categorize items (songs, pictures, web links, products, etc.). Social tagging systems (STSs) can provide three different types of recommendations: They can recommend 1) tags to users, based on what tags other users have used for the same items, 2) items to users, based on tags they have in common with other similar users, and 3) users with common social interest, based on common tags on similar items. However, users may have different interests for an item, and items may have multiple facets. In contrast to the current recommendation algorithms, our approach develops a unified framework to model the three types of entities that exist in a social tagging system: users, items, and tags. These data are modeled by a 3-order tensor, on which multiway latent semantic analysis and dimensionality reduction is performed using both the Higher Order Singular Value Decomposition (HOSVD) metho...

• Type: Journal
• Year: 2010
• Where: TKDE
• Authors: Panagiotis Symeonidis, Alexandros Nanopoulos, Yannis Manolopoulos
• Keywords: Social Tagging, Social Tagging Systems, Tags, TKDE 2010