A Data mining approach to indirect inference

Consider a model with parameter phi, and an auxiliary model with parameter theta. Let phi be a randomly sampled from a given density over the known parameter space. Monte Carlo methods can be used to draw simulated data and compute the corresponding estimate of theta, say theta_tilde. A large set of tuples (phi, theta_tilde) can be generated in this manner. Nonparametric methods may be use to fit the function E(phi|theta_tilde=a), using these tuples. It is proposed to estimate phi using the fitted E(phi|theta_tilde=theta_hat), where theta_hat is the auxiliary estimate, using the real sample data. This is a consistent and asymptotically normally distributed estimator, under certain assumptions. Monte Carlo results for dynamic panel data and vector autoregressions show that this estimator can have very attractive small sample properties. Confidence intervals can be constructed using the quantiles of the phi for which theta_tilde is close to theta_hat. Such confidence intervals are found to have very accurate coverage.

Using free data mining software and clustering algorithms to find predictors from student qualifications

In this project a research both in finding predictors via clustering techniques and in reviewing the Data Mining free software is achieved. The research is based in a case of study, from where additionally to the KDD free software used by the scientific community; a new free tool for pre-processing the data is presented. The predictors are intended for the e-learning domain as the data from where these predictors have to be inferred are student qualifications from different e-learning environments. Through our case of study not only clustering algorithms are tested but also additional goals are proposed.

From the “Mining Triangle” to the “Greater Region“ (“Großregion”/”Grande Région”). The Institutionalisation of the “SaarLorLux” Euroregion

Gairebé 182 milions d'ciutadans de la Unió Europea (= 37,5% de la població total) viuen en aproximadament 130 regions frontereres i transfrontereres. Aquestes regions contribueixen significativament al procés d'integració europea. Aquesta importància es documenta pel paquet dels Fons Estructurals 2007-2013, que ha estat presentat per la Comissió Europea i que va ser aprovat recentment pel Parlament Europeu. Considerant que la UE ha gastat uns 4875 € milions per a la cooperació transfronterera, transnacional i interregional en el marc de la iniciativa Interreg per al període 2000-2006, la cooperació territorial europea es convertirà en un dels tres objectius dels fons estructurals i rebrà € 7750000000 (5,57 milions d'euros per a la cooperació transfronterera només) per al període 2007-2013 (Comissió Europea, 2006a, 2006b). A part d'això, un nou conjunt de normes per a l'establiment d'una "agrupació europea de cooperació territorial" (AECT) ha estat adoptat i que facilitarà la cooperació transboundray, transnacional i interregional a la UE. Aquest treball s'ocuparà de les estructures de la institucionalització, la presa de decisions i l'execució i les polítiques de la "Gran Regió" / "Großregion" (d'ara endavant: GR o Gran Regió).

Mining and exploiting domain-specific corpora in the PANACEA platform

The objective of the PANACEA ICT-2007.2.2 EU project is to build a platform that automates the stages involved in the acquisition,production, updating and maintenance of the large language resources required by, among others, MT systems. The development of a Corpus Acquisition Component (CAC) for extracting monolingual and bilingual data from the web is one of the most innovative building blocks of PANACEA. The CAC, which is the first stage in the PANACEA pipeline for building Language Resources, adopts an efficient and distributed methodology to crawl for web documents with rich textual content in specific languages and predefined domains. The CAC includes modules that can acquire parallel data from sites with in-domain content available in more than one language. In order to extrinsically evaluate the CAC methodology, we have conducted several experiments that used crawled parallel corpora for the identification and extraction of parallel sentences using sentence alignment. The corpora were then successfully used for domain adaptation of Machine Translation Systems.

Capital formation in machinery and industrialization. Chile 1844-1938

The present paper revisits an old theme in Latin American and Chilean economic history; the early industrialization in the XIX - XX centuries. The difference with previous approaches is the elaboration of new quantitative series of Chilean machinery investment in the long run and its relative prices and composition, in the period when some authors have sited the beginning of the industrialization in the continent. Initial findings, based on the participation of capital formation in machinery imports and GDP, do not reinforce the idea of early industrialization in Chile.

Capital formation in machinery in Latin America, 1890-1930

Investment in machinery is a key aspect in the analysis of long-term economic growth during the era of the spread of industrialisation. But, historiography has only revealed what the pace of capital accumulation was in a few Latin American economies. This article offers continuous (annual) and consistent series on the magnitude of this investment in all of the Latin American countries for the period at the height of the first globalisation, 1890-1930. The paper gives special attention to comparative analysis, showing the differences that exist at the heart of the Latin American community, in the levels of capital formation in machinery as well as in the national development of this over time. The differences in the levels appear very indicative of the unequal degree of development reached by these economies. This article puts to test the hypothesis of intraregional divergence, obtaining the tentative result that there was divergence until 1913, but that there was convergence from 1914-1930.

Iron mining in Goa (India) : an interdisciplinary study

En aquest article es presenten breument els diferents capítols d’un treball interdisciplinari per tal d’entendre el context de prohibició de la mineria de ferro a Goa a finals del 2012 i proporcionar la informació necessària per tal d’orientar i gestionar la presa de decisions sobre l’activitat minera en un futur. Els sis primers capítols consisteixen en l’estudi del medi abiòtic, medi biòtic, fluxos de materials, aspectes socials, aspectes econòmics i finalment aspectes polítics. En canvi, en els dos últims capítols s'avaluen i es gestionen els impactes ambientals de la mineria mitjançant, per una banda, una anàlisi DPSIR i, d'altra banda, es proposen tres escenaris per integrar les diferents variables i fomentar la participació en la presa de decisions. S’ha dut a terme una extensa recerca mitjançant la recopilació de dades, entrevistes i visites a les zones d’estudi d’interès per tal d’entendre el conflicte de la mineria a Goa.

Destination image of Girona: an online text-mining approach

The main objective of this Master Thesis is to discover more about Girona’s image as a tourism destination from different agents’ perspective and to study its differences on promotion or opinions. In order to meet this objective, three components of Girona’s destination image will be studied: attribute-based component, the holistic component, and the affective component. It is true that a lot of research has been done about tourism destination image, but it is less when we are talking about the destination of Girona. Some studies have already focused on Girona as a tourist destination, but they used a different type of sample and different methodological steps. This study is new among destination studies in the sense that it is based only on textual online data and it follows a methodology based on text-miming. Text-mining is a kind of methodology that allows people extract relevant information from texts. Also, after this information is extracted by this methodology, some statistical multivariate analyses are done with the aim of discovering more about Girona’s tourism image

Educational data mining and learning analytics : Clasificación de las matriculaciones de A.D.E. en la UOC

Trabajo de investigación que realiza un estudio clasificatorio de las asignaturas matriculadas en la carrera de Administración y Dirección de Empresas de la UOC en relación a su resultado. Se proponen diferentes métodos y modelos de comprensión del entorno en el que se realiza el estudio.

Educational Data Mining: cerrando el círculo del proceso de aprendizaje en entornos virtuales

Development of methods to explore data from educational settings, to understand better the learning process.

Data mining and mall users profile

Marketing scholars have suggested a need for more empirical research on consumer response to malls, in order to have a better understanding of the variables that explain the behavior of the consumers. The segmentation methodology CHAID (Chi-square automatic interaction detection) was used in order to identify the profiles of consumers with regard to their activities at malls, on the basis of socio-demographic variables and behavioral variables (how and with whom they go to the malls). A sample of 790 subjects answered an online questionnaire. The CHAID analysis of the results was used to identify the profiles of consumers with regard to their activities at malls. In the set of variables analyzed the transport used in order to go shopping and the frequency of visits to centers are the main predictors of behavior in malls. The results provide guidelines for the development of effective strategies to attract consumers to malls and retain them there.