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This is the first in-depth study of information retrieval approaches applied to match-making systems such as a dating service.

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This research was divided in 3 parts: Study 1: this part of the study demonstrates that singles spend too much time searching for options online for too little payoff in offline dates.

Study 2: they came to the conclusion that users desire information about experiential attributes (sense of humor or rapport), but online dating sites contain primarily searchable attributes, such as income, religion, background...

The researchers of this study described a recommender system they implemented and performed a quantitative comparison of two collaborative filtering (CF) and two global algorithms.

Results showed that collaborative filtering recommenders significantly outperform global algorithms used by dating sites.The benefits of the proposed methodology with respect to traditional matchmaking baseline systems are shown by an extensive evaluation carried out using data gathered from a real online dating service.This analysis also provides deep insights into the aspects of matchmaking that are important for presenting highly relevant matches.To accomplish that the author presented two groups of participants a variety of questionnaires where they had to indicate their preferences for a partner.The first group of single students demonstrated a prevailing desire for a kind, considerate, and honest partner with a keen sense of humor.Online dating communities are a growing industry tailored specifically to users who are looking for a romantic partner, connection, or encounter.