F
Fernando A. Mikic-Fonte
Researcher at University of Vigo
Publications - 36
Citations - 703
Fernando A. Mikic-Fonte is an academic researcher from University of Vigo. The author has contributed to research in topics: Computer science & Recommender system. The author has an hindex of 8, co-authored 26 publications receiving 536 citations.
Papers
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Journal ArticleDOI
A hybrid content-based and item-based collaborative filtering approach to recommend TV programs enhanced with singular value decomposition
Ana Belen Barragans-Martinez,Enrique Costa-Montenegro,Juan C. Burguillo,Marta Rey-López,Fernando A. Mikic-Fonte,Ana Peleteiro +5 more
TL;DR: The proposed hybrid approach (which combines content-filtering techniques with those based on collaborative filtering) also provides all typical advantages of any social network, such as supporting communication among users as well as allowing users to add and tag contents, rate and comment the items, etc.
Journal ArticleDOI
Blended e-assessment
Martin Llamas-Nistal,Manuel J. Fernández-Iglesias,Juan Gonzalez-Tato,Fernando A. Mikic-Fonte +3 more
TL;DR: A tool combining the paper-pen exams and digital assessment and grading, which enables both formative and summative assessment, and also facilitates the transition from classical paper-and-pen-based assessment scenarios to digital ones is presented.
Journal ArticleDOI
A Systematic Review of Commercial Smart Gloves: Current Status and Applications.
TL;DR: A review of current commercial smart gloves focusing on three main capabilities: (i) hand and finger pose estimation and motion tracking, (ii) kinesthetic feedback, and (iii) tactile feedback is provided in this paper.
Proceedings ArticleDOI
moreTourism: Mobile recommendations for tourism
Marta Rey-López,Ana Belen Barragans-Martinez,Ana Peleteiro,Fernando A. Mikic-Fonte,Juan C. Burguillo +4 more
TL;DR: In this paper, the authors introduce a hybrid recommendation platform providing information about tourist resources depending on the user profile, location, schedule and the amount of time for visiting interest points isolated or combined in a route.
Journal ArticleDOI
Exploiting Social Tagging in a Web 2.0 Recommender System
Ana Belen Barragans-Martinez,Marta Rey-López,Enrique Costa Montenegro,Fernando A. Mikic-Fonte,Juan C. Burguillo,Ana Peleteiro +5 more
TL;DR: A novel tag-based recommender is presented to enhance the recommending engine by improving the coverage and diversity of the suggestions by using information obtained from social tagging to improve the recommendations.