Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-10-02T23:37:05Z No. of bitstreams: 1 ThiagoCorreiaPereira_DISSERT.pdf: 849760 bytes, checksum: 18b8f71b02ed28bbc81789242e6e17b4 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-10-09T19:56:01Z (GMT) No. of bitstreams: 1 ThiagoCorreiaPereira_DISSERT.pdf: 849760 bytes, checksum: 18b8f71b02ed28bbc81789242e6e17b4 (MD5) / Made available in DSpace on 2017-10-09T19:56:01Z (GMT). No. of bitstreams: 1 ThiagoCorreiaPereira_DISSERT.pdf: 849760 bytes, checksum: 18b8f71b02ed28bbc81789242e6e17b4 (MD5) Previous issue date: 2017-04-12 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / Devido ao grande volume de dados gerados pelo crescimento de aplica??es que prov?m novas informa??es, tanto em volume quanto em variedade, t?cnicas cada vez mais eficientes s?o exigidas para classific?-los e process?-los. Uma t?cnica muito utilizada ? o agrupamento de dados, cujo objetivo ? extrair conhecimento dos dados atrav?s da divis?o de entidades em subconjuntos homog?neos e/ou bem separados. Crit?rios podem ser utilizados para expressar a classifica??o dos dados. Dentre eles, um crit?rio frequentemente utilizado ? a soma m?nima das dist?ncias euclidianas quadr?ticas, do ingl?s, minimun sum-of-squares clustering (MSSC). Neste crit?rio, entidades s?o elementos no espa?o n-dimensional. O problema de agrupamento de dados pelo MSSC ? NP-?rduo, logo heur?sticas s?o t?cnicas extremamente ?teis para este tipo de problema. Este trabalho prop?e novas heur?sticas, baseadas na busca de vizinhan?as vari?veis gerais, do ingl?s, general variable neighborhood search (GVNS). Tamb?m ? proposto neste trabalho, a adapta??o da heur?stica reformulation descent (RD) para o problema MSSC, na forma de duas variantes, de forma in?dita na literatura. Os experimentos computacionais mostram que as variantes GVNS propostas neste trabalho apresentam melhores resultados, para inst?ncias grandes. / Due to the large volume of data generated by the growth of applications that provide new information, both in volume and variety, more efficient techniques are required to classify and processes them. A widely used technique is data grouping whose aim is to extract characteristics of the entities dividing them into homogeneous and/or well separated subsets. Many different criteria can be used to express the data classification. Among them, a commonly used criteria is the minimun sum-of-squares clustering (MSSC). In this criterion, entities are elements in n-dimensional Euclidean space. The data clustering problem by MSSC is NP-hard, then heuristics are extremely useful techniques for this type of problem. This work proposes new heuristics, based on the general variable neighborhood search (GVNS). Also proposed in this work is the adaptation of the heuristic reformulation descent (RD) to the MSSC problem, in the form of two variants, unapplied to this problem before in literature. The computational experiments show that the GVNS variants proposed in this work present better results, in large instances, than the current state of the art.

Syftet är att undersöka motiven årskortinnehavare har till att besöka Trelleborgs FF:s hemmamatcher. Med hjälp av en enkätundersökning kommer årskortsinnehavare att undersökas och kategoriseras med hjälp av modellen Motivation scale for sport consumption.Empirin har samlats in genom enkätundersökning på Trelleborgs FF:s nuvarande årskortsinnehavare och sedan bearbetats genom det teoretiska ramverket. Trails och James (2001) Motivation scale for sport consumption (MSSC) var det teoretiska ramverk som låg till grund för den enkät som utformades för att undersöka motiven för Trelleborgs FF:s årskortsinnehavare. Denna studie visade att de mest betydande motivet till att besöka Trelleborgs FF:s hemmamatcher var, för årskortsinnehavarena, att de har en emotionell koppling till laget. När laget presterar bra känner årskortsinnehavarna en känsla av prestation. En star emotionell koppling till laget och klubben. En av de minst betydande aspekterna för för årskortsinnehavarna var hur matcheventet var utformat. Det fanns få skillnader mellan då olika åldersgrupperna som undersöktes i denna studie. De skillnader som hittades visade att den äldsta (>68år) och yngsta (16–30 år) åldersgruppen, tillskillnad från övriga åldersgrupperna, ansåg att den estetiska skönheten som förknippas med Trelleborgs FF:s hemmamatcher samt att utveckla kunskap om spelet var av betydelse. Utöver detta var motiven liknande oavsett åldersgrupp. Denna studie ger en indikation på att det finns potentiella årskortsinnehavare som uteblir på grund av matcheventets utformning. Potentiella årskortsinnehavare med andra motiv än de som idag besöker eventet. Matcheventet hade med fördel kunnat ändrats för att attrahera fler årskortsinnehavare. / The purpose is to investigate the motives of season ticket holders to visit Trelleborg's FF home games. With the help of a survey, season ticket holders will be examined and categorized using the model Motivation scale for sport consumption.The data was collected through a survey of Trelleborgs FF:s current season ticket holders and then processed through the theoretical framework.Trails and James (2001) The Motivation Scale for Sport Consumption (MSSC) was the theoretical framework that formed the basis of the survey designed to examine the motives of Trelleborg's FF season ticket holders.This study showed that the most significant reason for visiting Trelleborgs FF:s home games was, for the season ticket holders, that they have an emotional connection with the team. When the team performs well, the season ticket holders feel a sense of accomplishment. A star emotional connection to the team and the club. One of the least significant aspects was, for the season ticket holders, how the match event was designed.There were few differences between the different age groups examined in this study. The differences found showed that the oldest (>68 years) and youngest (16-30 years) age groups, in contrary to the other age groups, considered that the aesthetic beauty associated with Trelleborgs FF:s home games and developing knowledge about the game of football was significant. In addition, the motives were similar regardless of age group.This study gives an indication that there are potential season ticket holders, with other motivational factors, that are absent due to the design of the match event. The match event could have been changed to attract more season ticket holders.

When a company includes a new technology or innovation into their value proposition, customers may perceive it as an enhancement or deterioration. This phenomenon was explored in this study with a case study of a present case in the esports industry. Research have shown that AI (Artificial Intelligence) technology can be used to predict which team is going to win in a match in the esports game DotA 2. A prototype AI called Znipe Sense was developed and analyzed during this study to answer the question: How can a predictive AI affect the value proposition of live esports consumption? Znipe Sense was included into Znipe Esports’ value proposition during a tournament in February 2018. It was observed that Znipe Sense could predict outcomes of professional matches with a higher accuracy than human experts. The observations of Znipe Sense, an interview with experienced players, interviews with business professionals and internal company documents were used as empirical material for the analysis. How Znipe Sense affected the value proposition was analyzed through the factors: Performance, Ease-of-use, Reliability, Flexibility and Affectivity, also known as the PERFA framework. It was concluded that a predictive AI can enhance the value proposition of live esports consumption through the Performance and Ease-of-use factors, and it would not affect the value proposition through Reliability or Flexibility. However, in the analysis of the Affectivity factor it was identified that there is a risk related to negative effects of gambling addiction that could deteriorate the value proposition. / När ett företag inkluderar en ny teknik eller innovation i sitt värdeerbjudande kan kunderna uppleva det som en förbättring eller försämring. Detta fenomen undersöktes i denna studie med en fallstudie av ett aktuellt fall i esportsindustrin. Forskning har visat att AI (Artificiell Intelligens) teknik kan användas för att förutsäga vilket lag som kommer att vinna i en match i esports spelet DotA 2. En AI prototyp, Znipe Sense, utvecklades och analyserades under denna studie för att svara på frågan: Hur kan ett prediktivt AI påverka värdeerbjudandet av live esports konsumtion? Znipe Sense inkluderades i Znipe Esports värdeerbjudande under en turnering i februari 2018. Det observerades att Znipe Sense var bättre än mänskliga experter på att förutse det vinnande laget i professionella matcher. Observationerna av Znipe Sense, en intervju med erfarna spelare, intervjuer med affärsfolk och interna företagsdokument användes som empiriskt material. Hur Znipe Sense påverkade värdeerbjudandet analyserades genom faktorerna: ”Performance”, ”Ease-of-use”, ”Reliability”, ”Flexibility” och ”Affectivity”, även känt som PERFA-ramverket. Slutsatsen visar på att ett prediktivt AI kan öka värdeerbjudandet av live esports konsumtion genom Performance och Ease- of-use faktorerna, och att värdeerbjudandet inte skulle påverkas genom Reliability och Flexibility. I analysen av Affectivity-faktorn identifierades emellertid att det finns en risk i relaterat till negativa effekter av spelberoende som kan försämra värdeerbjudandet.