Collaborative-Based Movie Recommender System—A Proposed Model

Author(s):  
Prajna Paramita Parida ◽  
Mahendra Kumar Gourisaria ◽  
Manjusha Pandey ◽  
Siddharth Swarup Rautaray
Author(s):  
Prajna Paramita Parida ◽  
Mahendra Kumar Gourisaria ◽  
Manjusha Pandey ◽  
Siddharth Swarup Rautaray

2013 ◽  
Vol 302 ◽  
pp. 787-791
Author(s):  
Lu Zhao ◽  
Rong Rong Yang ◽  
Meng Zhai ◽  
Feng Ming Liu

Delivering recommendation services are the trend of the future, so Recommender System varied very vital and widely applied in e-commerce websites to help customers in finding the items they want. A recommender system should be able to provide users with useful information about the items that might be interesting to them. The ability of immediately responding to changes in users preferences is a valuable asset for such systems. In recommender system, a variety of methods have been emerged as the basis for recommender. However, existing recommendation methods have the limitation. To overcome this limitation, we will propose new recommender system by combining the existing techniques. So, we firstly give an overview of recommender system for the future researches.


Author(s):  
David Baneres ◽  
Jordi Conesa

Is my professional knowledge outdated? Do I have the skills needed for the new challenges of the society? What knowledge do I lack to qualify for a job I like? What universities can I address to get knowledge that improves my employment expectations? These are relevant questions that all employees have done in any moment of their life. In addition, when there are high rates of unemployment and job offers that keep unfilled, the answers to these questions are even more relevant. Answering such questions open new opportunities for employed and unemployed people, by allowing them to design a formative plan according to their skills and expectations. It also provides evidences to employers about the skills and knowledge of the society, making them more aware of the skills of their potential future employees. The companies also will have more knowledge to design the professional career of their employees according to the company needs and the knowledge and skills of their employees. This paper proposes a system that helps people by showing which knowledge and skills a person misses for a given job position and what university courses the person can take to acquire the required skills and knowledge. The system has been implemented as a recommender system that helps users in planning their life-long learning. The paper shows the architecture of the proposed system, a case study to explain how it works, a survey to validate its usefulness and usability and some conclusions after its first experimentation.


2017 ◽  
Vol 7 (12) ◽  
pp. 1211 ◽  
Author(s):  
Khalid Haruna ◽  
Maizatul Akmar Ismail ◽  
Suhendroyono Suhendroyono ◽  
Damiasih Damiasih ◽  
Adi Pierewan ◽  
...  

2018 ◽  
Vol 7 (2.7) ◽  
pp. 671
Author(s):  
Kaleem SK ◽  
Rama Subbanna S

This paper presents adjustable speed generators for wind turbines. In order to improve the potential and performance of wind turbine system this paper proposes a concept DFIG. Generally wind nature is not fixed it varies linearly w.r.t time, hence, a MPPT controller is proposed in this paper. This paper presents the DFIG wind energy system. A Control strategy implemented and controlled by framing rotor reference frame axis in terms of direct and quadrature axis coordinates. A PI based RSC and GSC controllers are introduced to control the power through the wind system to grid. This proposed model is implemented and verified by using Matlab/Simulink.  


2019 ◽  
pp. 237-250
Author(s):  
Cristian González García ◽  
Daniel Meana-Llorián ◽  
Vicente García Díaz ◽  
Edward Rolando Núñez-Valdez

2019 ◽  
Vol 13 (03) ◽  
pp. 289-310
Author(s):  
Brandon Huynh ◽  
Adam Ibrahim ◽  
Yun Suk Chang ◽  
Tobias Höllerer ◽  
John O’Donovan

Augmented reality (AR) interfaces increasingly utilize artificial intelligence systems to tailor content and experiences to the user. We explore the effects of one such system — a recommender system for online shopping — which allows customers to view personalized product recommendations in the physical spaces where they might be used. We describe results of a [Formula: see text] condition exploratory study in which recommendation quality was varied across three user interface types. Our results highlight potential differences in user perception of the recommended objects in an AR environment. Specifically, users rate product recommendations significantly higher in AR and in a 3D browser interface, and show a significant increase in trust in the recommender system, compared to a web interface with 2D product images. Through semi-structured interviews, we gather participant feedback which suggests AR interfaces perform better due to their ability to view products within the physical context where they will be used.


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