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Lightweight tag-aware personalized recommendation on the social web using ontological similarity

Abstract:

With the rapid growth of social tagging systems, many research efforts are being put into personalized search and recommendation using social tags (i.e., folksonomies). As users can freely choose their own vocabulary, social tags can be very ambiguous (for instance, due to the use of homonyms or synonyms). Machine learning techniques (such as clustering and deep neural networks) are usually applied to overcome this tag ambiguity problem. However, the machine-learning-based solutions always ne...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/ACCESS.2018.2850762

Authors


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Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author
ORCID:
0000-0002-6719-7333
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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
ORCID:
0000-0002-7644-1668
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Name:
Office of Naval Research
Grant:
N00014-15-1-2742
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Name:
European Union
Grant:
690974
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Name:
Engineering and Physical Sciences Research Council
Grant:
EP/M025268/1
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Name:
Universidad Nacional del Sur
Publisher:
IEEE
Journal:
IEEE Access More from this journal
Publication date:
2018-06-26
Acceptance date:
2018-06-15
DOI:
ISSN:
2169-3536
Keywords:
Pubs id:
pubs:864967
UUID:
uuid:fa048d20-e1c1-4dbd-93fb-4d50093c6984
Local pid:
pubs:864967
Source identifiers:
864967
Deposit date:
2018-08-22

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