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Citations since 2016
4 Research Items
Recommendation system always involves huge volumes of data, therefore it causes the scalability issues that do not only increase the processing time but also reduce the accuracy. In addition, the type of data used also greatly affects the result of the recommendations. In the recommendation system, there are two common types of data namely implicit...
Companies should be willing to adopt new technologies and business models to be able to stay competitive in the changing world, both regionally and globally. However, the US forest sector industry, including wood furniture sector seems to be lagging when it comes to implementing digital technologies. This study proposes a design of Point of Interes...
Location recommendation system always involves huge volumes of data, therefore causes the scalability issues which not only increased processing time but cause reduced accuracy as well. Various techniques of recommendation system were developed to overcome this problem. Collaborative filtering is a technique that has a high accuracy in the loc...
Currently, face recognition system is growing sustainably on a larger scope. A few years ago, face recognition was used as a personal identification with a limited scope, now this technology has grown in the field of security, in terms of preventing fraudsters, criminals, and terrorists. In addition, face recognition is also used in detecting ho...
Poster ini disusun sebagai pelaporan kinerja Program Kreativitas Mahasiswa Karsa Cipta Tahun 2014
I'm doing research on a recommendation system using the Gowalla dataset. However, the dataset has no location rating so I must generate that data into an implicit rating with a value of '1' for those who have visited the location and '0' for those who have never visited the location. How should I create that matrix with python?
I am looking for codec algorithms for compressing video like in youtube when upload video.