Accurate recommendation based on opinion mining
Current recommender systems are mainly based on customers' personal information and
online behavior. We find that those systems lack efficiency and accuracy. At the same time …
online behavior. We find that those systems lack efficiency and accuracy. At the same time …
TV predictor: personalized program recommendations to be displayed on SmartTVs
Switching through the variety of available TV channels to find the most acceptable program
at the current time can be very time-consuming. Especially at the prime time when there are …
at the current time can be very time-consuming. Especially at the prime time when there are …
Collaborative filtering recommendation based on dynamic changes of user interest
I Gasmi, H Seridi-Bouchelaghem… - Intelligent Decision …, 2015 - content.iospress.com
Collaborative filtering is probably the most familiar and most widely implemented
recommendation algorithm. However, traditional collaborative filtering methods focus only …
recommendation algorithm. However, traditional collaborative filtering methods focus only …
[LIBRO][B] Time-dependent recommender systems for the prediction of appropriate learning objects
C Krauss - 2018 - search.proquest.com
This dissertation deals with adaptive learning technologies which aim to optimize
Technology Enhanced Learning (TEL) offerings to fit the individual learner's needs. Thereby …
Technology Enhanced Learning (TEL) offerings to fit the individual learner's needs. Thereby …
[PDF][PDF] Rating systems with multiple factors
M Stanescu - Master's thesis, 2011 - Citeseer
Rating systems have been receiving increasing attention recently, especially after
TrueSkillTM was introduced (Herbrich et al., 2007). Most existing models are based upon …
TrueSkillTM was introduced (Herbrich et al., 2007). Most existing models are based upon …
Social preference ontologies for enriching user and item data in recommendation systems
Some of the known issues of recommendation algorithms are a result of the so called" Cold
Start Problem" that is caused by a lack of sufficient data of users, items or the content, which …
Start Problem" that is caused by a lack of sufficient data of users, items or the content, which …
A recommender system for software architecture decision making
K Brandner, R Weinreich - … of the 13th European Conference on …, 2019 - dl.acm.org
Making the right design decisions for a software system is a difficult task. Inappropriate
design decisions are often hard to reverse and can lead to high costs and a poor quality of …
design decisions are often hard to reverse and can lead to high costs and a poor quality of …
Preference ontologies based on social media for compensating the cold start problem
Recommendation systems leverage future internet services to predict personalized
recommendations for products, services, media entities or other offerings. Based on the …
recommendations for products, services, media entities or other offerings. Based on the …
A novel recommendation system with collective intelligence
Academic resources on web include courses, educational videos, scientific literatures,
experts, peers and all of the useful stuff for research. It is crucial for researchers especially …
experts, peers and all of the useful stuff for research. It is crucial for researchers especially …
Social computing research map
Online society has triggered social computing which is an interdisciplinary that takes a
computational approach to the study and modelling of social interactions and …
computational approach to the study and modelling of social interactions and …