[Notes] Tommaso Di Noia at #SSSW2013

Tools and Techniques

Recommender systems

Input: Set of users + set of items + rating matrix.
Problem - given user, predict rating for an item.

In real world, recommendation matrix data is sparse.

Can use hybrid approaches.

Collaborative RS:

Knowledge-based RS:

User-based collaborative recommendation:

Item-based collaborative recommendation:

Content-based RS:

Using LOD

To mitigate lack of information/descriptions about concepts/entities.

Recommender systems are usually vertical, but LD lets you easily build a multi-domain recommender system.

To avoid noisy data, you have to filter it before feeding your RS.

Freebase.

Tiapolo

Vector space model for LOD

🏷 http://vocab.amy.so/blog#Done http://vocab.amy.so/blog#Done linked data notes phd recommendations recommender systems semantic web summer school semantic web tools semantic web sssw13 sssw2013 tommaso di noia

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