A unified framework for providing recommendations in social tagging systems based on ternary semantic analysis
MetadataShow full item record
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) method and the Kernel-SVD smoothing technique. We perform experimental comparison of the proposed method against state-of-the-art recommendation algorithms with two real data sets (Last.fm and BibSonomy). Our results show significant improvements in terms of effectiveness measured through recall/precision. © 2006 IEEE.
Showing items related by title, author, creator and subject.
Marinho LB; Hotho A; Jäschke R; Nanopoulos A; Rendle S; Schmidt-Thieme L; Stumme G; Symeonidis P (Springer Science & Business Media, 2012)Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize ...
Marinho LB; Nanopoulos A; Schmidt-Thieme L; Jäschke R; Hotho A; Stumme G; Symeonidis P (Springer US, 2011)The new generation of Web applications known as (STS) is successfully established and poised for continued growth. STS are open and inherently social; features that have been proven to encourage participation. But while ...
Papadimitriou A; Symeonidis P; Manolopoulos Y (Kluwer Academic Publishers, 2012)Recommender systems usually provide explanations of their recommendations to better help users to choose products, activities or even friends. Up until now, the type of an explanation style was considered in accordance to ...