Fuzzy AHP and TOPSIS in cross domain collaboration Recommendation with fuzzy visualization representation
—Cross domain collaboration recommendation method is proposed by combining fuzzy Analytic Hierarchy Process (AHP), fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and fuzzy network graph for interactive visualization method. Existing cross-domain recommendation ta...
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| Main Authors: | , |
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| Format: | Article |
| Published: |
International Association of Computer Science and Information Technology
2020
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| Online Access: | http://psasir.upm.edu.my/id/eprint/79964/ http://www.ijml.org/index.php?m=content&c=index&a=show&catid=110&id=1179 |
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| Summary: | —Cross domain collaboration recommendation
method is proposed by combining fuzzy Analytic Hierarchy
Process (AHP), fuzzy Technique for Order Preference by
Similarity to Ideal Solution (TOPSIS), and fuzzy network graph
for interactive visualization method. Existing cross-domain
recommendation tackles the problem of sparsity, scalability,
cold-start and serendipity issues found in single-domain,
therefore the combination of fuzzy AHP and TOPSIS with
visualization method may be able to give decision makers a
quick start to initiate cross-domain collaborations. The
proposed method is applied to the DBLP bibliographic citation
dataset that consists of 10 domains in the field of computer
science. Results show that the combination of fuzzy AHP and
TOPSIS enables decision makers to find several authors from
across domains that consist of 2.2 million publications in less
than 3 minutes. The combination method will be represented in
fuzzy visualization technique for fuzzy data. The establishment
of the cross domain recommendation will set a stage for efficient
preparation for researchers who are interested to venture into
other domains to increase their research competency. |
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