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Finding an image from a large set of images is an extremely difficult problem. One solution is to label images manually, but this is very expensive, time consuming and infeasible for many applications. Furthermore, it the labeling process depends on the semantic accuracy in describing the image. For this purpose, many Content based Image Retrieval (CBIR)(More)
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Forecasting hotel arrivals and occupancy is an important component in hotel revenue management systems. In this paper we propose a new Monte Carlo simulation approach for the arrivals and occupancy forecasting problem. In this approach we simulate the hotel reservations process forward in time, and these future Monte Carlo paths will yield forecast(More)
received considerable amount of attention in the machine learning community due its potential in reducing the need for expensive labeled data. In this work we present a new method for combining labeled and unlabeled data based on classifier ensembles. The model we propose assumes each classifier in the ensemble observes the input using different set of(More)
The prediction of stock market is considered a non-trivial problem in the financial arena. In the last few years many sophisticated models were developed to predict the stocks in order to achieve a maximum profit. Fuzzy models are one of the powerful methods that are used in this field. This paper proposes a fuzzy engine model that acts as an expert(More)