Analysis of panoramio photo tags in order to extract land use information

In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.

“Private label products: A category analysis”

The presented dissertation was developed within a partnership between Nova School of Business and Economics and the Portuguese retailer Sonae MC. The main objective of the study was to develop an analysis for the confectionary category to identify potential development opportunities for new Private Label products. In order to do so, the starting point was to understand how the confectionery market was behaving, followed by and understanding of Continente’s performance in that market. Aiming to point out development opportunities, the analysis was split between the subcategories – Chocolate, Chewing Gums and Sweets. The Subcategory performance was assessed in terms of sales, number of SKU’s, Private Label weight and it market position in terms of share. For the potential development opportunities a comparison between the top selling Branded Product and the competitors’ position was developed, in order to establish a reasonable size and retail price for such products. Key Word: Private Label, Branded Products, Continente, Sonae MC, Retail, SKU’s, Sales, Price, Market Share,