Abstract
Fuzzy AHP and TOPSIS in Cross Domain Collaboration Recommendation with Fuzzy Visualization Representation
Highlights
Cross domain collaborations has garnered much interest from researchers in the field of data mining and knowledge discovery in the recent years
Given the lack of cross domain collaboration recommendation tool available out in the market, a cross domain recommendation framework represented in fuzzy visualization is proposed
We aimed to develop a cross domain collaboration recommendation framework to solve multi-criteria decision making (MCDM) problems based on fuzzy analytic hierarchy process [6] and fuzzy Technique for Order Performance by Similarity to Ideal Solution [7] methods
Summary
Cross domain collaborations has garnered much interest from researchers in the field of data mining and knowledge discovery in the recent years. While the research in this area is flourishing, there is still very limited success in terms of realization for general research use. In UPM, cross domain collaboration are still initiated through word of mouth. A tool that can recommend possible collaboration among diversified fields is very much beneficial. There is increasing need for researchers to do cross domain collaboration as it allows researchers to enter a new field of research, keep their research skills up to date and the opportunity to learn other domain research language, growing speed and rewards. Given the lack of cross domain collaboration recommendation tool available out in the market, a cross domain recommendation framework represented in fuzzy visualization is proposed
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