Recommender System Framework for Academic Choices: Personality Based Recommendation Engine (PBRE)

2016 ◽  
Author(s):  
Muhammad Fahim Uddin ◽  
Soumita Banerjee ◽  
Jeongkyu Lee
Keyword(s):  
Recommender System ◽  
System Framework ◽  
Academic Choices

A Two-Step Best-Worst Method (BWM) and K-Means Clustering Recommender System Framework

2021 ◽  
pp. 29-40
Author(s):  
Saeed Najafi-Zangeneh ◽  
Naser Shams-Gharneh ◽  
Ali Arjomandi-Nezhad
Keyword(s):  
Recommender System ◽  
System Framework ◽  
Best Worst Method

Context-Awareness in Ensemble Recommender System Framework

2021 ◽  
Author(s):  
Ahlem Drif ◽  
Houssem Eddine Zerrad ◽  
Hocine Cherifi
Keyword(s):  
Recommender System ◽  
Context Awareness ◽  
System Framework

scholarly journals User-Review Oriented Social Recommender System for Event Planning

2020 ◽  
Vol 25 (5) ◽  
pp. 669-675
Author(s):  
Rahul Kumar Singh ◽  
Pardeep Singh ◽  
Gourav Bathla
Keyword(s):  
Recommender System ◽  
User Satisfaction ◽  
Recommendation System ◽  
Hybrid Approach ◽  
Social Commerce ◽  
System Framework ◽  
User Comments ◽  
Filtering Technique ◽  
Event Based ◽  
User Review

Recommender system is used to suggest product or topic based on user’s interest. Existing recommender system have focused on books, product, music etc. The problem in existing recommender system is that wedding/event based suggestions are not available. In the modern information era; storage, communication has been a challenge due to information veracity, volume, and velocity. Due to the constant and exponential growth of information, the utilization of information for context-oriented services is not productive. In this paper, a wedding planner recommender system framework has been proposed based on hybrid approach i.e., content based, collaborative filtering technique. The motive of proposed framework is to generate user-specific recommendations for different tasks related to the event specially wedding event, analyzed from the user comments on his social networking portal. Its main objective is to assist the user for organizing the events by suggesting specific vendors needed to arrange the event activities. Also, it would enhance the sales of location sensitive products in social commerce. The trial study conducted using a set of Facebook users is carried out to validate the proposed recommendation system framework. The success of the proposed framework is reported in terms of the level of user satisfaction achieved.

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