Sistema de Medida de Confianca para Selecc ¸ ˜ ao de Empresas em Sistemas B2B

TLDR: The designing and specification of a trust and contextual information aggregation model, intended to be a reliable alternative to the trust aggregation models already existing, and trying to set apart from those by including rules to emulate human common sense regarding trust building, and mechanisms to obtain a recommendation grade concerning how likely is a potential partner to perform as the authors desire in the fulfilment of a given contract.

Abstract: The study of trust aggregation mechanisms to assist the selection of companies in Business-to-Business systems, is becoming increasingly important to researchers in the areas of Multi-Agent Systems and Electronic Business, because it has been proved that it can provide means to increase the performance and reliability of the existing electronic business communities, by endowing them with human-like social defence mechanisms. The study we present in this document concerns the designing and specification of a trust and contextual information aggregation model, intended to be a reliable alternative to the trust aggregation models already existing, and trying to set apart from those by including rules to emulate human common sense regarding trust building, and mechanisms to obtain a recommendation grade concerning how likely is a potential partner to perform as we desire in the fulfilment of a given contract. This dissertation has three main parts. In the first, we present the trust and contextual information model, showing how we use an S-shaped curve to aggregate the past contract results of a given entity. From there we can retrieve a degree of trust which represents, in an abstract and simplified way, how likely is a given entity to fulfil the next contract, given how well she fulfilled the previous ones. The aggregation of contextual information can act as a disambiguation tool, because the information of the past contracts is treated concerning the context in which they were celebrated, providing, this way, a mean to assess if a given company is the most adjusted to do business with, regarding the specificities of the contract, and independently of how much trust do we deposit in them. In the second part we specify the application that we developed to simulate the process of company selection. This application implements the models that we propose as solution together with a third one, developed by another research group, to compare the performance and utility of our model. We simulate a fabric market, in which a group of buyers needs to buy certain quantities from sellers. In this process, each buyer is going to need the degree of trust and the degree of recommendation for each candidate seller, deciding which one(s) to buy from depending on that information. In the third part we demonstrate and analyze the results that we got from the simulations we have made. We developed three kinds of validation tests for the models: how fast were they identifying the companies violating fewer contracts, how well they react to an abrupt company behaviour change, and how much will the use of a recommendation grade affect the process of selecting a business partner. The results we got from the simulations show that our system for trust and contextual information measure represents a reliable option as a trust aggregation models, since, when compared to other model, it proves to be capable of selecting more times the best business partner, which understandably ends up in fewer violated contracts by the selected seller and higher business utility for the buyer.