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Semantic Matchmaking as Non-Monotonic Reasoning: A Description Logic Approach

arXiv.org Artificial Intelligence

Matchmaking arises when supply and demand meet in an electronic marketplace, or when agents search for a web service to perform some task, or even when recruiting agencies match curricula and job profiles. In such open environments, the objective of a matchmaking process is to discover best available offers to a given request. We address the problem of matchmaking from a knowledge representation perspective, with a formalization based on Description Logics. We devise Concept Abduction and Concept Contraction as non-monotonic inferences in Description Logics suitable for modeling matchmaking in a logical framework, and prove some related complexity results. We also present reasonable algorithms for semantic matchmaking based on the devised inferences, and prove that they obey to some commonsense properties. Finally, we report on the implementation of the proposed matchmaking framework, which has been used both as a mediator in e-marketplaces and for semantic web services discovery.


Semantic Matchmaking as Non-Monotonic Reasoning: A Description Logic Approach

Journal of Artificial Intelligence Research

Matchmaking arises when supply and demand meet in an electronic marketplace, or when agents search for a web service to perform some task, or even when recruiting agencies match curricula and job profiles. In such open environments, the objective of a matchmaking process is to discover best available offers to a given request. We address the problem of matchmaking from a knowledge representation perspective, with a formalization based on Description Logics. We devise Concept Abduction and Concept Contraction as non-monotonic inferences in Description Logics suitable for modeling matchmaking in a logical framework, and prove some related complexity results. We also present reasonable algorithms for semantic matchmaking based on the devised inferences, and prove that they obey to some commonsense properties. Finally, we report on the implementation of the proposed matchmaking framework, which has been used both as a mediator in e-marketplaces and for semantic web services discovery.


EOMM: An Engagement Optimized Matchmaking Framework

arXiv.org Artificial Intelligence

Matchmaking connects multiple players to participate in online player-versus-player games. Current matchmaking systems depend on a single core strategy: create fair games at all times. These systems pair similarly skilled players on the assumption that a fair game is best player experience. We will demonstrate, however, that this intuitive assumption sometimes fails and that matchmaking based on fairness is not optimal for engagement. In this paper, we propose an Engagement Optimized Matchmaking (EOMM) framework that maximizes overall player engagement. We prove that equal-skill based matchmaking is a special case of EOMM on a highly simplified assumption that rarely holds in reality. Our simulation on real data from a popular game made by Electronic Arts, Inc. (EA) supports our theoretical results, showing significant improvement in enhancing player engagement compared to existing matchmaking methods.


'Dota 2' Matchmaking Update Explained: Linked Phone Number, Solo Queue And More

International Business Times

Valve has rolled out the Matchmaking Update for "Dota 2." It brings a lot of changes to the free-to-play multiplayer online battle arena video game. On Thursday, the Dota Team announced via the "Dota 2" blog the arrival of the new update that improves the matchmaking experience in the game. Perhaps the biggest change that this update brings is the required linking of phone numbers to the Steam accounts of players in order for them to play Ranked matchmaking. The feature is added to prevent players from using multiple accounts since the team said that this just creates "a negative matchmaking experience at all skill brackets." With this new rule in place, players are given up to two weeks starting this Thursday to register a number to their account.


Municipal-run services using big data for matchmaking

The Japan Times

One day in May, a woman in her 40s was browsing a tablet computer at a municipality-funded matchmaking center, searching for a prospective husband. She was surprised; the computer suggested candidate she wouldn't have otherwise considered. "It recommends people who were under my radar," she said at the matchmaking center run by the city of Matsuyama, Ehime Prefecture. "I have a wider range of options." The woman, who asked to remain anonymous, was one of many seeking to boost their marriage prospects through a local government matchmaking program.