Recommendation systems are one of the information personalisation approach which is used to suggest relevant items and information according to user preferences and objective behaviors. As far as context-aware recommender systems are concerned, such systems consider user current context and needs while recommending items and information.What could be the potential applications of such systems in various domains? Please provide reference to the articles which could best represent that particular domain.
a context-aware recommender system is considered the hottest area in the recommender system. It 's not like traditional one depends only on item and user entities,it considers any contextual information, such as time, place and etc. It is also important to bring the contextual information into the recommendation process in order to recommend items to users under certain circumstances. for example in the online restaurant, if you log in the page in the morning , the recommender system will suggest a breakfast meal based on your preferences. The same thing happens when you log in at evening , the recommender system will suggest a dinner meal.
you can check the book
Recommender Systems Handbook, chapter 7, by Francesco Ricci et al.
It gives examples of applications in context-aware recommender systems.
a context-aware recommender system is considered the hottest area in the recommender system. It 's not like traditional one depends only on item and user entities,it considers any contextual information, such as time, place and etc. It is also important to bring the contextual information into the recommendation process in order to recommend items to users under certain circumstances. for example in the online restaurant, if you log in the page in the morning , the recommender system will suggest a breakfast meal based on your preferences. The same thing happens when you log in at evening , the recommender system will suggest a dinner meal.
you can check the book
Recommender Systems Handbook, chapter 7, by Francesco Ricci et al.
It gives examples of applications in context-aware recommender systems.
Yousra Elhakeem,
Your answer is very helpful, however, i would like to explore the area of context aware recommender systems in more detail. According to your view it could be used in the field of restaurant while suggesting meal to an end user. I have observed that context aware recommender systems are most commonly used in domains of movies, locations, restaurants but its usage in other domains such as research articles, books is limited. What could be the reasons and why these systems are not yet introduced in these domains? Also, there are some domains for which online dataset is not available, only few of domains having standard datasets. What could be the reasons behind all these issues and factors?
Context aware is very difficult snice it always change based situation or time or location or etc. If you take for example book recommending, it's need to recommend different books during same day/week/month. This is creating a lot data and need a lot of processing. So if this done by Amazon with more than 8 million users, this case ahead and leads to big data issue. I remember saw an interview with the author of the book I recommend to you above (Francesso Ricci) he mentioned that using context aware add more dimensions and can sparsity.
Yousra Elhakeem,
I agree with you that introducing contextual information cause serious research issues. But, i need to explore such areas where context aware recommender systems have been introduced. If you have experienced such systems or articles mention here in your comments please.
Thanks
Context-Aware Recommender Systems, by Gediminas Adomavicius, Bamshad Mobasher, Francesco Ricci, and Alex Tuzhilin
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