Una scossa all'economia: le conseguenze del sisma dell'Aquilano. Traduzione dall'inglese in italiano di un articolo di ricerca economica ed esperienza di collaborazione con gli autori.

The aim of this dissertation is to provide a translation from English into Italian of a specialised scientific article published in the Cambridge Working Papers in Economics series. In this text, the authors estimate the economic consequences of the earthquake that hit the Abruzzo region in 2009. An extract of this translation will be published as part of conference proceedings. The main reason behind this choice is a personal interest in specialised translation in the economic domain. Moreover, the subject of the article is of particular interest to the Italian readership. The aim of this study is to show how a non-specialised translator can tackle with such a highly specialised translation with the use of appropriate terminology resources and the collaboration of field experts. The translation could be of help to other Italian linguists looking for translated material in this particular domain where English seems to be the dominant language. In order to ensure consistent terminology and adequate style, the document has been translated with the use of different resources, such as dictionaries, glossaries and specialised corpora. I also contacted field experts and the authors of text. The collaboration with the authors proved to be an invaluable resource yet one to be carefully managed. This work is divided into 5 chapters. The first deals with domain-specific sublanguages. The second gives an overview of corpus linguistics and describes the corpora designed for the translation. The third provides an analysis of the article, focusing on syntactical, lexical and structural features while the fourth presents the translation, side-by-side with the source text. The fifth comments on the main difficulties encountered in the translation and the strategies used, as well as the relationship with the authors and their review of the published text. Appendix I contains the econometric glossary English – Italian.

Cookgle, motore di ricerca per ricette culinarie

Cookgle e il prototipo di un motore di ricerca per ricette culinarie. Scopo della dissertazione e mostrare i punti chiave e i problemi riscontrati durante la progettazione dell'applicativo per l'architettura ad alto livello. Questo concept rappresenta il primo mattone delle successive costruzioni, volte ad ottenere un motore di ricerca per ricette culinarie in grado di indicizzare tutte le ricette presenti nel web.

Google Images German Federal Court Entscheidung vom 29.04.2010, I ZR 69/08 With an English Introduction

The long-awaited verdict by the German Federal Court of Justice towards Google image search has drawn much attention to the problem of copyright infringement by search engines on the Internet. In the past years the question has arose whether the listing itself in a search engine like Google can be an infringement of copyright. The decision is widely seen as one of the most important of the last years. With significant amount of effort, the German Fede- ral Court tried to balance the interests of the right holders and those of the digital reality.

Herramientas e indicadores SEO: características y aplicación al análisis de cibermedios

La búsqueda es una de las actividades centrales en el mundo digital y, por tanto, uno de los elementos clave en el análisis de cibermedios, ya que una parte de sus audiencias y de sus ingresos procede de las páginas de resultados de los buscadores (SERP). En este trabajo, presentamos algunas de las herramientas de análisis de posicionamiento SEO más utilizadas con el fin de considerar su aplicación en estudios académicos sobre cibermedios. Aplicamos los nueve indicadores más importantes de estas herramientas a la página principal de cuatro cibermedios generalistas espanoles con el fin de estimar su viabilidad como indicadores alternativos al PageRank y otros indicadores de Google.

Finding relevant search engine results:a minimax linear programming approach

For a submitted query to multiple search engines finding relevant results is an important task. This paper formulates the problem of aggregation and ranking of multiple search engines results in the form of a minimax linear programming model. Besides the novel application, this study detects the most relevant information among a return set of ranked lists of documents retrieved by distinct search engines. Furthermore, two numerical examples aree used to illustrate the usefulness of the proposed approach.

SemSearch:a search engine for the semantic web

Existing semantic search tools have been primarily designed to enhance the performance of traditional search technologies but with little support for ordinary end users who are not necessarily familiar with domain specific semantic data, ontologies, or SQL-like query languages. This paper presents SemSearch, a search engine, which pays special attention to this issue by providing several means to hide the complexity of semantic search from end users and thus make it easy to use and effective.

A Digital Library of Folklore Songs and Keyword-Based Search Engine

ACM Computing Classification System (1998): H3.3, H.5.5, J5.

Regrouping metric-space search index for search engine size adaptation

This work contributes to the development of search engines that self-adapt their size in response to fluctuations in workload. Deploying a search engine in an Infrastructure as a Service (IaaS) cloud facilitates allocating or deallocating computational resources to or from the engine. In this paper, we focus on the problem of regrouping the metric-space search index when the number of virtual machines used to run the search engine is modified to reflect changes in workload. We propose an algorithm for incrementally adjusting the index to fit the varying number of virtual machines. We tested its performance using a custom-build prototype search engine deployed in the Amazon EC2 cloud, while calibrating the results to compensate for the performance fluctuations of the platform. Our experiments show that, when compared with computing the index from scratch, the incremental algorithm speeds up the index computation 2–10 times while maintaining a similar search performance.

Self-adapting parallel metric-space search engine for variable query loads

This research focuses on automatically adapting a search engine size in response to fluctuations in query workload. Deploying a search engine in an Infrastructure as a Service (IaaS) cloud facilitates allocating or deallocating computer resources to or from the engine. Our solution is to contribute an adaptive search engine that will repeatedly re-evaluate its load and, when appropriate, switch over to a dierent number of active processors. We focus on three aspects and break them out into three sub-problems as follows: Continually determining the Number of Processors (CNP), New Grouping Problem (NGP) and Regrouping Order Problem (ROP). CNP means that (in the light of the changes in the query workload in the search engine) there is a problem of determining the ideal number of processors p active at any given time to use in the search engine and we call this problem CNP. NGP happens when changes in the number of processors are determined and it must also be determined which groups of search data will be distributed across the processors. ROP is how to redistribute this data onto processors while keeping the engine responsive and while also minimising the switchover time and the incurred network load. We propose solutions for these sub-problems. For NGP we propose an algorithm for incrementally adjusting the index to t the varying number of virtual machines. For ROP we present an ecient method for redistributing data among processors while keeping the search engine responsive. Regarding the solution for CNP, we propose an algorithm determining the new size of the search engine by re-evaluating its load. We tested the solution performance using a custom-build prototype search engine deployed in the Amazon EC2 cloud. Our experiments show that when we compare our NGP solution with computing the index from scratch, the incremental algorithm speeds up the index computation 2{10 times while maintaining a similar search performance. The chosen redistribution method is 25% to 50% faster than other methods and reduces the network load around by 30%. For CNP we present a deterministic algorithm that shows a good ability to determine a new size of search engine. When combined, these algorithms give an adapting algorithm that is able to adjust the search engine size with a variable workload.

A domain-specific search engine for the construction sector

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.