Market Outcomes under Different Recommender Systems: Experimental Evidence from an Online Dating Service

2019 ◽  
Author(s):  
Yuwei Hsieh ◽  
Kuan-Ming Chen
Keyword(s):  
Experimental Evidence ◽  
Recommender Systems ◽  
Online Dating ◽  
Market Outcomes

BlindDate recommender: A context-aware ontology-based dating recommendation platform

2018 ◽  
Vol 45 (5) ◽  
pp. 573-591 ◽  
Author(s):  
Miguel Ángel Rodríguez-García ◽  
Rafael Valencia-García ◽  
Ricardo Colomo-Palacios ◽  
Juan Miguel Gómez-Berbís
Keyword(s):  
Recommender Systems ◽  
Romantic Relationship ◽  
Online Dating ◽  
Romantic Partners ◽  
Context Aware ◽  
Semantic Technologies ◽  
Real World Data ◽  
Data Set ◽  
Hybrid Techniques ◽  
F Measure

Online dating sites have become popular platforms for those individuals who utilise the Internet to develop a personal or romantic relationship. Unlike typical recommenders systems, which attempt to suggest items such as films, songs, books and so on. According to a user’s interests, dating recommender systems provide services that people can use to find potential romantic partners. Since these services have a higher expectancy of users, online dating sites are considering the introduction of recommender systems in order to build an improved dating network. Different kinds of techniques based on content-based, collaborative filtering or hybrid techniques exist. In this article, we introduce BlindDate recommender, a context-based platform that utilises semantic technologies to describe users’ preferences more precisely. We utilise DBPedia repositories to obtain information that is subsequently used to enrich a previously generated ontology model. The instances inserted into the ontology enable the matching algorithms that we have generated to identify potential matches between users. In order to validate the performance of the platform, we utilise a real-world data set that has produced relevant results enhancing the accuracy compared with other well-known approaches and identifying the discriminant parameters used in the dating domain. More specifically, the proposed approach attains 0.79, 0.8 and 0.55 in the I-Precision, I-Recall and I-F-measure, respectively, when employed in separate topics.

scholarly journals Subsidy Incidence in Privately Negotiated Spot Markets: Experimental Evidence

2019 ◽  
Vol 51 (02) ◽  
pp. 219-234
Author(s):  
Mohammad Maksudur Rahman ◽  
Christopher T. Bastian ◽  
Chian Jones Ritten ◽  
Owen R. Phillips
Keyword(s):  
Experimental Evidence ◽  
Statistical Difference ◽  
Experimental Methods ◽  
Spot Markets ◽  
Market Outcomes ◽  
Economic Agents ◽  
Subsidy Incidence

AbstractWe use experimental methods to investigate subsidy incidence, the transfer of subsidy payments from intended recipients to other economic agents, in privately negotiated spot markets. Our results show that market outcomes in treatments with a subsidy given to either buyers or sellers are significantly different from both a no-subsidy treatment and the competitive prediction of a 50% subsidy incidence. The disparity in incidence across treatments relative to predicted levels suggests that incidence equivalence does not hold in this market setting. Moreover, we find no statistical difference in market outcomes when benefits are framed as a “subsidy” versus a schedule shift.

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