Traditional skill ratings are not suitable for new types of games. We developed a general skill rating framework for games which do not discriminate players based on their skill. This class of games is widely present in the world. We use Bayesian statistics to convert aggregate data about the player's performance to a percentile rank describing his skill. The system is applicable to both single-player and multiplayer games with binary and non-binary endings. The rating formulas do not contain any arbitrary constants. We have tested the system in simulations and on real game data, and we outline its possible applications.

[pt] Matchmaking pode ser entendido, de forma bem geral, como um processo de busca dos possíveis casamentos entre demandas e ofertas, em um dado domínio de aplicação. Esse trabalho define uma infra- estrutura de software para matchmaking, cujas instâncias do domínio estão descritas com base numa ontologia qualquer. A infra-estrutura proposta é composta por dois componentes: o framework Matching Module, que define uma plataforma flexível e extensível para tratar processos de matchmaking de forma independente de domínio, e a OntoAPI, uma API de serviços de acesso a dados anotados semanticamente, que utilizem RDF, RDFS ou OWL como linguagens de descrição. / [en] Matchmaking should be understood, in a general way, as a search process for matchings between demand and supply requests within an application domain. This work defines a matchmaking software infrastructure whose domain instances are described in terms of an ontology. The proposed infrastructure has two major components: the framework Matching Module, which defines a flexible and extensible platform for dealing with matchmaking process, independently of the domain, and the OntoAPI, an API providing access services to semantically annotated data, that use RDF, RDFS or OWL as description languages.

[pt] Este trabalho apresenta um serviço de matchmaking (MMS) cujo objetivo é facilitar encontros entre pessoas que estejam geograficamente próximas e que tenham interesses similares. Para que pessoas se encontrem e eventualmente colaborem, o MMS analisa perfis de usuários portadores de dispositivos móveis, que estejam co-localizados e indica quais usuários possuem um maior grau de similaridade entre os seus perfis. Os perfis são descritos como ontologias no formato OWL (Web Ontology Language), onde assuntos de interesse podem ser relacionados a regiões simbólicas. As informações sobre localizações são obtidas por meio da interação do MMS com o serviço de inferência de localização (Location Inference Service - LIS), que faz parte da arquitetura MoCA (Mobile Collaboration Architecture). O serviço MMS tem uma arquitetura cliente/ Servidor. O servidor MMS provê o serviço de matchmaking em dois modos: o síncrono e o assíncrono. O primeiro modo permite que usuários façam consultas para encontrar pessoas com interesses similares na localização em que se encontram. O segundo modo permite que usuários sejam notificados sempre que apareça algum outro usuário na sua vizinhança que tenha interesses similares aos dele. O cliente MMS provê acesso ao serviço e permite a edição dos perfis de interesse específicos para cada localização. / [en] This work presents a matchmaking service (MMS) to enable meetings among co-localized people sharing similar interests. To make possible meetings and collaborations, the MMS analyses profiles of co- localized users using mobile devices, and indicates which users have a high degree of similarity among their profiles. The profiles are described using ontologies in OWL format (web ontology language), where the subjects of interest may be related with symbolic regions. The information about localization is obtained through interactions of MMS with a location service (Location Inference Service - LIS) present in MoCA architecture (Mobile Collaboration Architecture). The MMS service is built in a client/ Server architecture. The MMS provides the matchmaking service in two modes: synchronous and asynchronous. The synchronous mode allows users to request MMS to find people with similar interest in the same location. The asynchronous mode allows users to subscribe to the MMS service to receive automatic notifications when the MMS finds people in the neighborhood with similar interests. The MMS client provides access to the service and allows edition of users` profiles of interest for each localization.

Service oriented computing is crucial to a large and growing number of computational undertakings. Central to its approach are the open and network-accessible services provided by many different organisations, and which in turn enable the easy creation of composite workflows. This leads to an environment containing many thousands of services, in which a programmer or automated composition system must discover and select services appropriate for the task at hand. This discovery and selection process is known as matchmaking. Prior work in the field has conceived the problem as one of sufficiently describing individual services using formal, symbolic knowledge representation languages. We review the prior work, and present arguments for why it is optimistic to assume that this approach will be adequate by itself. With these issues in mind, we examine how, by reformulating the task and giving the matchmaker a record of prior service performance, we can alleviate some of the problems. Using two formalisms—the incidence calculus and the lightweight coordination calculus—along with algorithms inspired by information retrieval techniques, we evolve a series of simple matchmaking agents that learn from experience how to select those services which performed well in the past, while making minimal demands on the service users. We extend this mechanism to the overlooked case of matchmaking in workflows using multiple services, selecting groups of services known to inter-operate well. We examine the performance of such matchmakers in possible future services environments, and discuss issues in applying such techniques in large-scale deployments.

With the capacity to connect millions of singles through the virtual world, online matchmaking has altered the traditional, face-to-face romantic relationship initiation process. Users of online matchmaking sites have easy access to thousands of available singles and can communicate with partners before ever meeting face-to-face. Specific mechanisms by which online matchmaking environments operate are likely to distort both users’ appraisals of other users and users’ appraisals of themselves. This phenomenon in dating has left researchers to speculate about the effectiveness of romantic relationship initiation in such a context, and for relationships that are successfully formed online, whether the effects of online matchmaking extend beyond the relationship initiation process to influence the subsequent progression of romantic relationships. Seventy-five single men and women were recruited and agreed to subscribe to the online matchmaking site Match.com for 30 days. Participants completed measures assessing their individual background characteristics, sociosexual orientation, personality and attachment. In the event that participants scheduled a first date with someone they met through Match.com, they completed pre and post-date measures assessing idealistic distortion of, attention to, and ease of finding alternative dating partners. Upon completion of their 30 days in the study, participants completed a follow-up questionnaire assessing the degree to which they idealistically distorted themselves to other users and their overall satisfaction and experience using Match.com. Logistic regression analyses revealed that the more users’ distorted the vitality and attractiveness of dating partners the less likely users were to experience a second date initiated by the dating partner. Future studies need to consider that traditional models of relationship initiation are out-dated and not applicable to the study of relationship initiation and progression in the context of online matchmaking. Relationship researchers need to investigate: gender differences in filtering potential partners, the function of filtering in such a context, the developmental progression of filtering and the subsequent potential heightened importance of physical attraction verses the importance of compatibility in predicting relationship initiation in the online matchmaking environment. Additionally, future research should involve comparisons of various matchmaking services’, should utilize larger sample sizes and should follow participants for a longer period of time. / text

Matchmaking is an essential part of many modern online multiplayer games and is used by game developers to give the players the best possible online gaming experience. However, since video games have become more complex, traditional matchmaking systems like TrueSkill have reached their limits in predicting match outcomes. An extensive literature survey on engagement and balance in video games as well as an analysis of Battlefield 4 player data showed that balance can have a significant impact on player engagement. This lays the basis for the new matchmaking approach that is presented in this thesis. It is developed for the online First Person Shooter game Battlefield 4, with the goal of increasing player engagement by balancing online multiplayer matches. The developed matchmaking system is based on regression models, which use player performance metrics to predict the balance of online multiplayer matches. The experimental evaluations of the developed models show that the quality of the prediction results are influenced by the complexity of the different game modes available in Battlefield 4. Furthermore the historical Battlefield 4 game report data, which is used for building the predictive models, shows that this complexity as well as imbalances in the game design add significant noise to balance predictions. Both evaluated regression models – Linear Regression and Multivariate Adaptive Regression Splines – showed similar prediction errors within statistically expected deviation. Additionally it is shown that both methods have significantly smaller errors than the TrueSkill system, when predicting the outcome of games in Team Death Match or Conquest mode. The features that resulted in the lowest errors are commonly used in online First Person Shooter games. Hence the findings of this thesis can not only improve the matchmaking of Battlefield 4, but also benefit other video games of the same genre. / Matchmaking är en viktig del av många onlinespel och används av spelutvecklare för att ge spelare en bättre spelupplevelse. På senare tid har spelen blivit mer komplexa och traditionella matchmakingsystem som TrueSkill klarar inte längre förutse utfall av matcher. Andra studier som avhandlar spelaktivitet och balans i matcher visar att spelare har ökad aktivitet om deras matcher har varit jämna. Det går även att dra samma slutsatser från speldata i Battlefield 4. Syftet med denna uppsats är att utveckla och utvärdera en ny modell för matchmaking i spelet Battlefield 4 som medför bättre balans i matcher och därmed ökar spelaktiviteten. Den utvecklade matchmaking-modellen baseras på regressionmodeller som använder historiska speldata för enskilda spelare för att förutse jämnheten i matcher. Utvärderingen av den utvecklade modellen visar att förmågan att förutse matcher beror på hur hur komplext spelläget i Battlefield 4 är. Det framgår också efter att ha tittat på historiska spelrapporter att förutom komplexiteten i spelläget så påverkar också obalans i speldesignen förmågan att förutse matcher. Båda utvärderade regressionsmodeller – linjär regression och Multivariate Adaptive Regression Splines – har liknande förmåga att förutse utfallet av matcher där ingen är signifikant bättre än den andra. Dessutom visas att båda modellerna förutser matchresultaten för spellägena Team Death Match och Conquest signifikant bättre än TrueSkill. De här spellägena är vanliga i denna typen av spel så resultaten i denna uppsats är inte isolerade till Battlefield 4 utan går att applicera på många spel i samma genre.

Research question: How can a regional centre of excellence develop new opportunities for digital collaboration? Purpose: The aim of the study is to explore new opportunities for collaboration through interviews of six member companies to the center of excellence Automation Region. The interest in the study is to investigate the value and possible obstacles and needs the members experience in the service / services provided. In turn, with the help of theoretical support, the aim is to counteract and improve the perceived weaknesses Automation Region has through digital solutions. Method: The research design of the study is a qualitative case study based on an inductive approach. The primary empirical data was derived from semi-structured interviews on six members to Automation Region. The remaining empirical data was collected with previously conducted surveys of AR and notes/comments from members. Conclusion: To promote innovative collaboration, it is proposed to build a community, benefit from crowdsourcing and implement a matchmaking-system to drive collaboration and innovation. The proposals are applied and made available as digital services that are delivered by Automation Region to the members. / Forskningsfråga: Hur kan ett regionalt kompetenscentrum utveckla nya möjligheter för digital samverkan? Syfte: Studiens syfte är att utforska nya möjligheter för samverkan genom att utgå från sex intervjuer från medlemsföretag till kompetenscentret Automation Region. Intresset i studien är att undersöka värdet samt möjliga hinder och behov medlemmarna upplever i tjänsten/tjänster som tillhandahålls. I sin tur, med hjälp av teoretiskt stöd, syftas att motverka och förbättra de svagheter Automation Region upplevs ha genom digitala lösningar. Metod: Studien har utgått ifrån en kvalitativ fallstudie med sex semistrukturerade intervjuer, sekundärdata från uppdragsgivare och erfarenhetsbaserad empiri från författarnas egna tid hos uppdragsgivaren. Slutsats: För att främja innovativ samverkan föreslås att bygga upp en community, dra nytta av crowdsourcing samt implementera ett matchmaking-system för att driva fram samverkan och innovation. Förslagen tillämpas och tillgängliggörs som digitala tjänster som levereras av Automation Region till medlemmarna.

O presente trabalho apresenta uma abordagem aperfeiçoada para medir similaridade entre Serviços Web Semânticos através de um algoritmo baseado em ontologia. O trabalho se trata de um aperfeiçoamento por pegar como base o algoritmo de Liu (LIU et al., 2009) e nele fazer uma pequena mudança que resulta em melhorias significativas em certos cenários. Este algoritmo utiliza informação das categorias ESPE (Entradas, Saídas, Pré-condições, Efeitos), procurando por informações presentes nessas categorias, analisando como os conceitos estão relacionados na taxonomia da ontologia. A escolha do trabalho de Liu ocorreu devido a experimentos realizados em trabalhos anteriores ao desta dissertação (MAAMAR et al., 2011)(MAAMAR et al., 2011). Nesses experimentos, foi constatado que o algoritmo não antigia um desempenho satisfatório, foi então que se levantou uma hipótese de aperfeiçoamento deste algoritmo. Experimentos realizados utilizando um conjunto de dados contendo 1083 Serviços Web Semânticos em OWL-S mostram que essa abordagem aperfeiçoada aumenta a precisão do algoritmo, diminuindo desta forma o número de falsos positivos recuperados nos resultados, mantendo uma boa revocação. Nestes experimentos, foram implementados o algoritmo original de Liu e a versão modificada apresentada nesta dissertação. Além disso, este trabalho apresenta quais parâmetros utilizar para configurar o algoritmo e atingir melhor precisão, revocação e f-measure. / The current work presents an improved approach for an ontology-based semantic web service matchmaking assessment algorithm. This work is based on Liu’s algorithm LIU et al. (2009) providing a small change which results in a significant enhancement at some scenarios. The algorithm uses information from IOPE (Inputs, Outputs, Preconditions, Effects) categories, searching for information about the concepts located in these categories, analyzing how they are related in an ontology taxonomy. Liu’s work was chosen due to experiments that were done in works previous to this dissertation (MAAMAR et al., 2011)(MAAMAR et al., 2011). During those experiments, it was realized that Liu’s algorithm did not achieve good results. Then, an hypothesis was raised for improving this algorithm. Experiments performed using a data set containing 1083 OWL-S semantic web services show that the improved approach increases the algorithm precision, diminishing the number of false positives in the retrieved results, and still having a good recall. For doing these experiments, Liu’s algorithm and this dissertation version of it were implemented. Furthermore, this work presents the parameters that were used to achieve better precision, recall and f-measure.

O presente trabalho apresenta uma abordagem aperfeiçoada para medir similaridade entre Serviços Web Semânticos através de um algoritmo baseado em ontologia. O trabalho se trata de um aperfeiçoamento por pegar como base o algoritmo de Liu (LIU et al., 2009) e nele fazer uma pequena mudança que resulta em melhorias significativas em certos cenários. Este algoritmo utiliza informação das categorias ESPE (Entradas, Saídas, Pré-condições, Efeitos), procurando por informações presentes nessas categorias, analisando como os conceitos estão relacionados na taxonomia da ontologia. A escolha do trabalho de Liu ocorreu devido a experimentos realizados em trabalhos anteriores ao desta dissertação (MAAMAR et al., 2011)(MAAMAR et al., 2011). Nesses experimentos, foi constatado que o algoritmo não antigia um desempenho satisfatório, foi então que se levantou uma hipótese de aperfeiçoamento deste algoritmo. Experimentos realizados utilizando um conjunto de dados contendo 1083 Serviços Web Semânticos em OWL-S mostram que essa abordagem aperfeiçoada aumenta a precisão do algoritmo, diminuindo desta forma o número de falsos positivos recuperados nos resultados, mantendo uma boa revocação. Nestes experimentos, foram implementados o algoritmo original de Liu e a versão modificada apresentada nesta dissertação. Além disso, este trabalho apresenta quais parâmetros utilizar para configurar o algoritmo e atingir melhor precisão, revocação e f-measure. / The current work presents an improved approach for an ontology-based semantic web service matchmaking assessment algorithm. This work is based on Liu’s algorithm LIU et al. (2009) providing a small change which results in a significant enhancement at some scenarios. The algorithm uses information from IOPE (Inputs, Outputs, Preconditions, Effects) categories, searching for information about the concepts located in these categories, analyzing how they are related in an ontology taxonomy. Liu’s work was chosen due to experiments that were done in works previous to this dissertation (MAAMAR et al., 2011)(MAAMAR et al., 2011). During those experiments, it was realized that Liu’s algorithm did not achieve good results. Then, an hypothesis was raised for improving this algorithm. Experiments performed using a data set containing 1083 OWL-S semantic web services show that the improved approach increases the algorithm precision, diminishing the number of false positives in the retrieved results, and still having a good recall. For doing these experiments, Liu’s algorithm and this dissertation version of it were implemented. Furthermore, this work presents the parameters that were used to achieve better precision, recall and f-measure.

O presente trabalho apresenta uma abordagem aperfeiçoada para medir similaridade entre Serviços Web Semânticos através de um algoritmo baseado em ontologia. O trabalho se trata de um aperfeiçoamento por pegar como base o algoritmo de Liu (LIU et al., 2009) e nele fazer uma pequena mudança que resulta em melhorias significativas em certos cenários. Este algoritmo utiliza informação das categorias ESPE (Entradas, Saídas, Pré-condições, Efeitos), procurando por informações presentes nessas categorias, analisando como os conceitos estão relacionados na taxonomia da ontologia. A escolha do trabalho de Liu ocorreu devido a experimentos realizados em trabalhos anteriores ao desta dissertação (MAAMAR et al., 2011)(MAAMAR et al., 2011). Nesses experimentos, foi constatado que o algoritmo não antigia um desempenho satisfatório, foi então que se levantou uma hipótese de aperfeiçoamento deste algoritmo. Experimentos realizados utilizando um conjunto de dados contendo 1083 Serviços Web Semânticos em OWL-S mostram que essa abordagem aperfeiçoada aumenta a precisão do algoritmo, diminuindo desta forma o número de falsos positivos recuperados nos resultados, mantendo uma boa revocação. Nestes experimentos, foram implementados o algoritmo original de Liu e a versão modificada apresentada nesta dissertação. Além disso, este trabalho apresenta quais parâmetros utilizar para configurar o algoritmo e atingir melhor precisão, revocação e f-measure. / The current work presents an improved approach for an ontology-based semantic web service matchmaking assessment algorithm. This work is based on Liu’s algorithm LIU et al. (2009) providing a small change which results in a significant enhancement at some scenarios. The algorithm uses information from IOPE (Inputs, Outputs, Preconditions, Effects) categories, searching for information about the concepts located in these categories, analyzing how they are related in an ontology taxonomy. Liu’s work was chosen due to experiments that were done in works previous to this dissertation (MAAMAR et al., 2011)(MAAMAR et al., 2011). During those experiments, it was realized that Liu’s algorithm did not achieve good results. Then, an hypothesis was raised for improving this algorithm. Experiments performed using a data set containing 1083 OWL-S semantic web services show that the improved approach increases the algorithm precision, diminishing the number of false positives in the retrieved results, and still having a good recall. For doing these experiments, Liu’s algorithm and this dissertation version of it were implemented. Furthermore, this work presents the parameters that were used to achieve better precision, recall and f-measure.