TOWARD A DISTRIBUTED DATA MINING SYSTEM FOR TOURISM INDUSTRY

Romania has a huge tourist’s potential, but currently it is too little valued and exploited. As a result, one of the strategic developments of the economy aimed the tourism industry. The strategic decisions are based on different trends obtained from sophtourism industry, data mining techniques, distributed databases

ALGORITHM FOR GENERALIZED GARMAN EQUATION IN OPTION PRICING OF A FINANCIAL DERIVATIVES WITH STOCHASTIC VOLATILITY MODELS

In our paper we build a reccurence from generalized Garman equation and discretization of 3-dimensional domain. From reccurence we build an algorithm for computing values of an option based on time, momentan volatility of support and value of support on afinancial derivatives, Black-Scholes PDE, Garman PDE, reccurence, algorithm

Data Dimensionality Reduction for Data Mining: A Combined Filter-Wrapper Framework

Knowledge Discovery in Databases aims to extract new, interesting and potential useful patterns from large amounts of data. It is a complex process whose central point is data mining, which effectively builds models from data. Data type, quality and dimensionality are some factors which affect performance of data mining task. Since the high dimensionality of data can cause some troubles, as data overload, a possible solution could be its reduction. Sampling and filtering reduce the number of cases in a dataset, whereas features reduction can be achieved by feature selection. This paper aims to present a combined method for feature selection, where a filter based on correlation is applied on whole features set to find the relevant ones, and then, on these features a wrapper is applied in order to find the best features subset for a specified predictor. It is also presented a case study for a data set provided by TERAPERS a personalized speech therapy system

ALGORITHM FOR GENERALIZED GARMAN EQUATION IN OPTION PRICING OF A FINANCIAL DERIVATIVES WITH STOCHASTIC VOLATILITY MODELS

In our paper we build a reccurence from generalized Garman equation and discretization of 3-dimensional domain. From reccurence we build an algorithm for computing values of an option based on time, momentan volatility of support and value of support on

Study of improving the customer relationship management by data mining applications

Companies must survive in a market, where are a lot of products and competitors which compete to gain the customers. In a such market there are some factors which influences the growing of the complexity of customer relationships. Some of these factors are: the compression of the marketing cycle times, the increasing of marketing costs, the avalanche of new products offering and the existence of niche competitors. The companies must react quickly to the challenges of these factors, reaction which consist in the right offer to the right person at the right time trough the right channel. CRM involves new ways of interacting with the customers which promises higher returns on investments for businesses by enhancing customer-oriented processes such as sales, marketing, and customer service. Data mining- techniques for automate detecting of relevant patterns in databases- helps companies build personal and profitable customer relationships by identifying and anticipating the needs of customers throughout the customer lifecycle

Big Data: Actuality and Challenges

The volume of data is constantly growing due to the explosion of machine-generated data and human involvement in social networks, especially in the last period in which the pandemic forced most activities to take place online. Big Data refers to storage, manipulation and analysis of this huge data sets that come from variety of sources and are too large and too heterogeneous to be traditionally processed. This paper gives an overview of Big Data sources, Big Data analytics, its applications, advantages and limitations, and challenges that Big Data has to face nowadays