Fintech

Technologies

• Big data
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Technologies
Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. This type of data requires a different processing approach called big data, which uses massive parallelism on readily-available hardware
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• Case-based Reasoning (CBR)
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Technologies
The case-based reasoining (CBR) is a paradigm that is based on the idea that similar problems have similar solutions. It draws on past experiences to solve new problems. Thus, if in a past moment it decided to solve a problem using a certain solution and once the solution is applied it achieves a certain result. Then it seems logical that, if a new problem is presented with characteristics similar to that previously solved in the past, it resorts to the acquired experience to give a solution. The acting model of the CBR system is known for the life cycle of the CBR system.
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• Cloud computing
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Technologies
Distributed systems and cloud computing have revolutionized traditional systems of communication and computing. The BISITE group has experience in distributed Artificial Intelligence, which joins concepts from two fields of knowledge: Artificial Intelligence and Distributed Systems. The field of Artificial Ingelligence (IA) attempts to understand intelligent entities. Additionally, it focuses on research in the field of Cloud Computing. The three fundamental points at the core of the group’s research are: Multiagent Systems, Distributed Resolution of Problems, and cloud computing systems. The basic problems studied within DAI. In line with this study, the team has worked on research projects in collaboration with companies such as INSA-IBM, among others.
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• Experts systems
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Technologies
An expert system is capable of storing the knowledge of an expert in a particular specialty and limited, and in turn to solve problems through logical deduction-induction. They capture the knowledge of an expert and try to imitate the process of reasoning when solving problems in a given domain.
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• Intelligent Modelling
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Technologies
The Intelligent Modelling is a revolutionary new approach to process modeling and pattern recognition, which is applicable to virtually any automated process. It captures the behavior of a process by building empirical models based on historical data. Deviations are catalogued into signatures to form patterns that are used to identify problems.
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• Multi-Agents System
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Technologies
One of the most representative fields in the study and development of systems of BISITE, is research on agent technology. It is a fact that the use of agents and multiagent systems for application development in dynamic and flexible environments is growing. In general, agents are being used in a variety of applications because they offer substantial advantages, including the naturalness of the model to conceptualize different types of software. Similarly, multi-agent systems represent a new way of analyzing, designing and implementing complex software systems. A multiagent system consists of several different autonomous agents interacting to achieve the desired function. Each agent performs a series of tasks and communicates with other agents to exchange information or demand a service. Both the agents and multiagent systems research fields are currently in full development, which are increasingly spending more resources.
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• Negotiation technologies
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Technologies
Negotiation is a process by which a group of entities try and come to a mutually acceptable agreement on some matter. Recently, however, there has been a surge of interest in automated negotiation systems that are populated with artificial agents (Nicholas R. Jennings)
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• Predictive algorithms
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Technologies
Predictive algorithms use an explicit process model to predict the behavior of the system response. For each time interval, the predictive algorithm determines a control sequence that optimizes future behavior.
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• Recommender systems
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Technologies
Recommender systems propose ranked lists of items (that are subsets of a larger collection) according to their presumed relevance to individual users. Relevance is determined from explicit and implicit user feedback such as ratings on items, commercial transactions or explicitly stated requirements (Zanker, M., Jessenitschnig, M)
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• Technology Enhanced Learning (TEL)
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Technologies
Research on Technology Enhanced Learning (TEL) investigates how information and communication technologies can be designed in order to support pedagogical activities.
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