All over the world, future parents are facing the task of finding a suitable given name for their children. Their choice is usually influenced by a variety of factors, such as the social context, language, cultural background and especially personal taste. Although this task is omnipresent, little research has been conducted on the analysis and application of interrelations among given names from a data mining perspective. Since 1999 the ECML PKDD embraces the tradition of organizing a Discovery Challenge, allowing researchers to develop and test algorithms for novel and real world datasets. The Discovery Challenge 20131 tackled the task of recommending given names in the context of the name search engine Nameling. It consisted of an offline and an online phase. In both phases, participants were asked to create a name recommendation algorithm that could provide suitable suggestions of given names to users of Nameling. More than 40 participants/teams registered for the challenge, of which 17 handed in predictions of the offline challenge. After the end of the offline phase 6 teams submitted a paper. All papers have been peer reviewed and can be found in these proceedings. The different approaches to the challenge are presented at the ECML PKDD workshop on September 27th, 2013, in Prague, Czech Republic. The online challenge ran until the day before the workshop and four teams successfully participated with implementations meeting all required criteria. Details of the two challenge tasks, winners of both phases and an overview of the main findings are presented in the first paper of these proceedings.


CEUR-WS.org/Vol-1120 - 20DC13 - ECML PKDD Discovery Challenge - Recommending Given Names 2013

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