Recommender system for online dating service

Abstract: The aim of the thesis is to research the utility of collaborative filtering based recommender systems in the area of dating services.The practical part of the thesis describes the actual implementation of several standard collaborative filtering algorithms and a system, which recommends potential personal matches to users based on their preferences (e.g. The collaborative filtering is built upon the assumption, that users with similar rating patterns will also rate alike in the future.The empirical comparison of the five methods on different recommendation quality criteria shows that no method is overwhelmingly better than the others and that a trade-off need be taken when choosing one for a live system.

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He founded Washington DC based Alta Plana Corporation, an information technology strategy consultancy, in 1997 and is longtime Tech Web contributor (Information Week, All Analytics, Internet Evolution, and before them, Intelligent Enterprise).

Lulu, a book publishing site, is in the news this week.

But there are many more sites for book reviews, self-publishing and exchange. Disclosure: Lulu currently has an ad campaign running on Mashable.

Types of collective intelligence Collective intelligence is shared or group intelligence that emerges from the collaboration, collective efforts, and competition of many individuals and appears in consensus decision making.

Each type of system has its own strengths and weaknesses.