What is it about?
Recommender Systems (RS) are software tools that use analytic technologies to suggest different items of interest to an end user. Linked Data is a set of best practices for publishing and connecting structured data on the Web. This paper presents a systematic literature review to summarize the state of the art in recommender systems that use structured data published as Linked Data for providing recommendations of items from diverse domains.
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Why is it important?
This paper gives not only a review of state of the art about recommender systems exploiting the knowledge of the web of data but also an example of how to perform a systematic literature review in the software field.
Perspectives
Currently, we are working on improving the algorithms used in Recommender Systems based on Linked Data through the implementation and application of Machine Learning algorithms.
PhD Cristhian Figueroa
Politecnico di Torino
Read the Original
This page is a summary of: A systematic literature review of Linked Data-based recommender systems, Concurrency and Computation Practice and Experience, January 2015, Wiley,
DOI: 10.1002/cpe.3449.
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