NDLI: A tag recommendation system for folksonomy

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A tag recommendation system for folksonomy

Content Provider	ACM Digital Library
Author	Zhang, Ning Tang, Jie Zhang, Yuan
Abstract	Social bookmarking tools become more and more popular nowadays and tagging is used to organize information and allow users to recall or search the resources. Users need to type the tags whenever they post a resource, so that a good tag recommendation system can ease the process of finding some useful and relevant keywords for users. Researchers have made lots of relevant work for tag recommendation systems, but those traditional collaborative systems may not perform well in the case of a new user and a new resource. To address this problem, we propose a tag recommendation system for two different cases. The first case is that the active user or active resource is a new one which has not appeared in the past while the second case is that the active user and resource has already been posted. In this paper, we present two different methods for these two cases: a content-based method and a graph-based method. We implement our tag recommendation system in a realworld academic Folksonomy system. In order to gain better results,we apply improvements and combinations of previous work in each of these two methods.and combinations of previous work in each of these two methods. We participated into the Discovery Challenge 2009 with the proposed methods. The results of our teams are within the top teams.
Starting Page	9
Ending Page	16
Page Count	8
File Format	PDF
ISBN	9781605588063
DOI	10.1145/1651437.1651440
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-11-02
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Language model Collaborative filtering Tag recommendation Topic model
Content Type	Text
Resource Type	Article

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