A comparison of data mining methods for mass real estate appraisal

We compare the performance of both hedonic and non-hedonic pricing models applied to the problem of housing valuation in the city of Madrid. Urban areas pose several challenges in data mining because of the potential presence of different market segments originated from geospatial relations. Among the algorithms presented, ensembles of M5 model trees consistently showed superior correlation rates in out of sample data. Additionally, they improved the mean relative error rate by 23% when compared with the popular method of assessing the average price per square meter in each neighborhood, outperforming commonplace multiple linear regression models and artificial neural networks as well within our dataset, comprised of 25415 residential properties.mass appraisal, real estate, data mining

Simulation and Control of Groups of People in Multi-modal Mobility

Tourism and transport are constantly growing and, with it, the movements of travellers. This entails two fundamental effects on which we must focus: control of mass tourism and the organization of transport. Good transport organization and travel planning avoid crowds and therefore mass tourism. This allows promoting sustainable tourism in which it is sought to offer a quality service to tourists taking care of the environment. In this thesis the objective is to manage the flow of groups of people through means of transport. This control of groups of people is aimed at customer satisfaction by offering quality tourism. On the one hand, the study focuses on the problem to mitigate the negative effects due to mass arrivals in touristic locations. A TEN network has been developed to define the optimal tours for different groups of tourists. A related mixed integer quadratic optimization model has been developed with three main objectives: it minimizes the maximum value of occupancy in the selected destinations to limit mass tourism, reduces the divergence between the proposed visit tour and one required by the tourist group and the overall duration of their visit, and a heuristic approach has been introduced. On the other hand, it has been implemented a railway scheduling and rescheduling problem introducing optimization-based and min-max approaches on the regional and high-speed railway network. The scheduling model defines the best schedules for a set of trains considering costumers\u2019 demand and the priority of the trains to cover the rail sections in case of conflict on the railway lines. Consecutively, the generated feasible timetables are used to minimize possible consequences due to events that may negatively affect the real time traffic management. The main contribution of this section is the introduction in the second approach the innovative concept to prioritize the train that can access on the block section in case of conflicts on the network

A comparison of data mining methods for mass real estate appraisal

We compare the performance of both hedonic and non-hedonic pricing models applied to the problem of housing valuation in the city of Madrid. Urban areas pose several challenges in data mining because of the potential presence of different market segments originated from geospatial relations. Among the algorithms presented, ensembles of M5 model trees consistently showed superior correlation rates in out of sample data. Additionally, they improved the mean relative error rate by 23% when compared with the popular method of assessing the average price per square meter in each neighborhood, outperforming commonplace multiple linear regression models and artificial neural networks as well within our dataset, comprised of 25415 residential properties

The Economics of Software Products: an Example of Market Failure

In this paper we examine pricing imperfections in software companies by analyzing the case of Microsoft, and we uncover the presence of pervasive dead-weight losses derived from the inability of the producer to achieve first degree price discrimination. Because the nature of software is such that it can be reproduced an infinite number of times at practically zero cost once the first copy is manufactured, the amount of these losses in terms of efficiency can be substantial, which opens the door for external intervention in the market. We finish by suggesting a simple policy rule in this direction, although the applicability may be limited to the theoretical realm, as it can distort the incentives of private enterprise as a provider of software products

A comparison of data mining methods for mass real estate appraisal

We compare the performance of both hedonic and non-hedonic pricing models applied to the problem of housing valuation in the city of Madrid. Urban areas pose several challenges in data mining because of the potential presence of different market segments originated from geospatial relations. Among the algorithms presented, ensembles of M5 model trees consistently showed superior correlation rates in out of sample data. Additionally, they improved the mean relative error rate by 23% when compared with the popular method of assessing the average price per square meter in each neighborhood, outperforming commonplace multiple linear regression models and artificial neural networks as well within our dataset, comprised of 25415 residential properties

Mineralogía y evolución de las pegmatitas graníticas de La Cabrera (Sistema Central Español)

En relación con el plutonismo granítico de La Cabrera se pueden distinguir varias clases de pegmatitas, atendiendo al tipo de granito que las origina, forma de emplazamiento y relación con el encajante. Estas pegmatitas están constituidas fundamentalmente por cuarzo, albita, feldespato potásico y micas, pudiendo ir acompañadas de cordierita, granate y turmalina. Ocasionalmente se ha constatado la presencia de apatito, rutilo, casiteria, gadolinita, thalenita y bavenita. Son características generales de estas pegmatitas la pobreza en ferromagnesianos, ausencia casi absoluta de minerales fosfatados, así como una gran escasez de moscovita que cuando aparece tiene un carácter tardío en relación con los principales minerales pegmatíticos s.s. Algunos cuerpos pegmatíticos presentan unos procesos evolutivos complejos que denotan una cierta actividad hidrotermal, continuada hasta una etapa de muy baja temperatura. Esta evolución cabe referirla a dos etapas principales: a) Etapa de formación de clinozoisita, prehnita, axinita. b) Etapa de formación de ceolitas. En relación con la primera de estas etapas y de una manera ocasional, pueden formarse algunos sulfuros, así como wolframita, schelita y fluorita. Aceptándose una presión menor de 2 kb durante la formación de estas pegmatitas, se discuten una serie de posibles reacciones para la formación de los nuevos minerales anteriormente citados, así como su posible intervalo termodinámico de cristalización

A Language Model based Job Recommender

Matching candidates to job openings is a hard real world problem of economic interest that thus far de es researchers' attempts to tackle it. Collaborative ltering methods, which have proven to be highly e ective in other domains, have a di cult time nding success when applied to Human Resources. Aside from the well known cold-start issue there are other problems speci c to the recruitment world that explain the poor results attained. In particular, fresh job openings arrive all the time and they have relatively short expiration periods. In addition, there is a large volume of passive users who are not actively looking for a job, but that would consider a change if a suitable o er came their way. The two constraints combined suggest that content based models may be advantageous. Previous attempts to attack the problem have tried to infer relevance from a variety of sources. Indirect information captured from web server and search engine logs, as well as eliciting direct feedback from users or recruiters have all been polled and used to construct models. In contrast, this thesis departs from previous methods and tries to exploit resume databases as a primary source for relevance information, a rich resource that in my view remains greatly underutilized. Relevance models are adapted for the task at hand and a formulation is derived to model job transitions as a Markov process, with the justi cation being based on David Ricardo's principle of comparative advantage. Empirical results are compiled following the Cran eld benchmarking methodology and compared against several standard competing algorithms

Polímeros de impresión molecular para la determinación de pesticidas

Tesis de la Universidad Complutense de Madrid, Facultad de Ciencias Químicas, Departamento de Química Analítica, leída el 27-02-2009Depto. de Química AnalíticaFac. de Ciencias QuímicasTRUEpu