عرض بسيط للتسجيلة

المؤلفRawashdeh, Majdi
المؤلفKim, Heung-Nam
المؤلفAlja'am, Jihad Mohamad
المؤلفEl Saddik, Abdulmotaleb
تاريخ الإتاحة2024-03-20T01:55:07Z
تاريخ النشر2013
اسم المنشورJournal of Intelligent Information Systems
المصدرScopus
الرقم المعياري الدولي للكتاب9259902
معرّف المصادر الموحدhttp://dx.doi.org/10.1007/s10844-012-0227-2
معرّف المصادر الموحدhttp://hdl.handle.net/10576/53259
الملخصNowadays social tagging has become a popular way to annotate, search, navigate and discover online resources, in turn leading to the sheer amount of user-generated metadata. This paper addresses the problem of recommending suitable tags during folksonomy development from a graph-based perspective. The proposed approach adapts the Katz measure, a path-ensemble based proximity measure, for the use in social tagging systems. We model a folksonomy as a weighted, undirected tripartite graph. We then apply the Katz measure to this graph, and exploit it to provide tag recommendations for individual users. We evaluate our method on two real-world folksonomies collected from CiteULike and Last.fm. The experimental results demonstrate that the proposed method improves the recommendation performance and is effective for both active taggers and cold-start taggers compared to existing algorithms.
راعي المشروعAcknowledgement This publication was made possible by a grant from the Qatar National Research Fund NPRP 09-052-5-003.
اللغةen
الناشرSpringer
الموضوعFolksonomy
Graph-based ranking
Link prediction
Social tagging
Tag recommendation
Tripartite graph
العنوانFolksonomy link prediction based on a tripartite graph for tag recommendation
النوعArticle
الصفحات307-325
رقم العدد2
رقم المجلد40
dc.accessType Abstract Only


الملفات في هذه التسجيلة

الملفاتالحجمالصيغةالعرض

لا توجد ملفات لها صلة بهذه التسجيلة.

هذه التسجيلة تظهر في المجموعات التالية

عرض بسيط للتسجيلة