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- W2183699523 abstract "Recommender systemsarosein viewof the information overload present innumerousdomains. Theso- called content-based recommenders offer products similar to thosetheusersliked inthepast. However, duetotheuseof syntactic similarity metrics, thesesystemselaborate overspecialized recommendations including productsvery similar tothose theuseralready knows.Inthis paper, wepresent a strategy thatovercomesoverspecialization by applying semantic reasoning techniques. Thankstothereasoning, our strategy discovers hugeamountsofknowledge abouttheuser's preferences, andcompares themwithavailable products ina moreflexible way,beyondtheconventional syntactic metrics. Theresulting reasoning-based strategy hasbeenexperimentally evaluated intheDigital TV domain.Our results show:(i) enhancedpersonalized recommendations, (ii)computational viability, and(iii) muchgreater accuracy. I.INTRODUCTION ~ ~~~~ ~ ~~~~d:rt *-rren / ACTORS BIOGRAPHY ROMANC OUNTRIES TRAVEL TOURISM (LO .E" @default.
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- W2183699523 date "2008-01-01" @default.
- W2183699523 modified "2023-09-25" @default.
- W2183699523 title "Providing Entertainment byContent-based Filtering and Reasoning inIntelligent Recommender Systems" @default.
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