オープンデータ関連のニュースです。
日本語
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English
We give guidelines to drive the choice of the feature selection technique, according to the needs of a specic recommendation scenario (i.e., maximize accuracy, maximize diversity). We investigate the impact of the integration of the knowledge coming from the LOD cloud in a graph-based recommendation framework. Thanks to the recent spread of the Linked Open Data (LOD) initiative, a huge amount of machine-readable knowledge encoded as RDF statements is today available in the so-called LOD cloud. Accordingly, a big effort is now spent to investigate to what extent such information can be exploited to develop new knowledge-based services or to improve the effectiveness of knowledge-intensive platforms as Recommender Systems (RS).
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