Hi everyone,
Is there a pertinents work on applying LOD (Linked Open Data), or ontologies, in a collaborative filtering.
Or, in other termes, how to introduce semantic data in a collaborative filtering.
Thanks,
Hi,
From literature collaborative filtering means "recommend user with the help of its neighbors likings"..
1. Pure collaborative filtering works only with User-Item preference matrix...i.e. either by User-User collaborative filtering or Item-Item collaborative filtering (methods using simple heuristics).
or by Matrix Factorization methods..[1]
In this if you want to exploit semantics, then you can use both User-Item preference and Item-Property matrix (generated from semantic data) parallely as mentioned in [2].
2. Other than point 1, if you want to utilize semantic information about users, you have to create it from yourself as this information is not openly available in Linked Open Data (LOD). Or may be you can try to use the semantic information provided by Facebook.
[1] Koren, Yehuda, Robert Bell, and Chris Volinsky. "Matrix factorization techniques for recommender systems." Computer 42.8 (2009): 30-37.
[2] Nidhi Kushwaha, Xudong Sun, O. P. Vyas, Artus Krohn-Grimberghe:
SemPMF: Semantic Inclusion by Probabilistic Matrix Factorization for Recommender System. PAAMS (Special Sessions) 2016: 327-334
Hi Mohammed,
I can refer following works that combines linked open data and recommendation systems.
Start by reading Tommaso Di Noia papers; he has an important work on the subject. Here papers that you can start with:
* Recommender Systems Meet Linked Open Data.
* Recommender Systems and Linked Open Data.
* Content-Based Recommendations via DBpedia and Freebase: A Case Study in the Music Domain.
Take a look on his papers here:
http://dblp.uni-trier.de/pers/hd/n/Noia:Tommaso_Di
You can also take a look on these papers:
[1] R. Meymandpour and J. G. Davis, “Enhancing Recommender Systems Using Linked Open Data-Based Semantic Analysis of Items,”
[2] A. Passant, “dbrec - Music Recommendations Using DBpedia,”
Dear Nasreddine and Nidhi,
Thanks for your help.
Nasreddine, i'm more interestind in collaborative filtering.
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