Une approche computationnelle du cadastre napoléonien de Venise

At the beginning of the 19th century, the Napoleonic administration introduced a new standardised description system to give an objective account of the form and functions of the city of Venice. The cadastre, deployed on a European scale, was offering for the first time an articulated and precise view of the structure of the city and its activities, through a methodical approach and standardised categories. With the use of digital techniques, based in particular on deep learning, it is now possible to extract from these documents an accurate and dense representation of the city and its inhabitants. By systematically checking the consistency of the extracted information, these techniques also evaluate the precision and systematicity of the surveyors’ work and therefore indirectly qualify the trust to be placed in the extracted information. This article reviews the history of this computational protosystem and describes how digital techniques offer not only systematic documentation, but also extraction perspectives for latent information, as yet uncharted, but implicitly present in this information system of the past.

Guidelines to Visualize Vessels in a Geographic Information System

Dario Rodighiero

In information systems the data representation covers a great importance. In fact the visualization of information is the last point of contact between the user and the information system. This is the space where the communication takes place. In real-time monitoring systems, this passage covers a great importance, especially for reasons related to the time and the transparency of relevant information. These factors are fundamental to vessel monitoring systems. This is the beginning where we start to define a guidelines manual, act to help specialists of information visualization in the vessel monitoring field, and in the GIS field more in general.

IEEE2010

A deep learning approach to Cadastral Computing

Sofia Ares Oliveira, Isabella Di Lenardo, Frédéric Kaplan, Bastien Solal Emile Tourenc

This article presents a fully automatic pipeline to transform the Napoleonic Cadastres into an information system. The cadastres established during the first years of the 19th century cover a large part of Europe. For many cities they give one of the first geometrical surveys, linking precise parcels with identification numbers. These identification numbers points to registers where the names of the proprietary. As the Napoleonic cadastres include millions of parcels , it therefore offers a detailed snapshot of large part of Europe’s population at the beginning of the 19th century. As many kinds of computation can be done on such a large object, we use the neologism “cadastral computing” to refer to the operations performed on such datasets. This approach is the first fully automatic pipeline to transform the Napoleonic Cadastres into an information system.

2019

Cognitive language engineering towards robust human-computer interaction

Vincenzo Pallotta

Intelligent information processing seems to be one of the most challenging task among those involved in human-computer interaction. A central issue is how to model the various types of interaction among artificial and natural entities at different levels of abstraction. On the one hand, models of interaction are required to better understand the communication phenomena. On the other, suitable languages and paradigms should provide powerful frameworks for developing computer-based applications. In this dissertation I focus on different aspects of the second problem, trying to develop a methodology for the design of interactive natural language applications (e.g. from question-answering to mixed-initiative dialogue). One of the main aspects I am concerned with in this work is the problem of their robustness. Several methods have been proposed for achieving robustness in natural language understanding, but these methods are sometimes hard to scale up or re-use in different applications. Moreover, they often concentrate on a single linguistic level of the processing rather than offering a global solution. I will set up a Language Engineering environment whose goal is to combine software engineering and cognitive aspects (e.g. aspects related to representation of a mental model of the speaker). Given its complexity, it is apparent that the problem can be solved only partially. I want to stress here that the main contribution of my work is a holistic perspective on the problem of natural language understanding. Rather than focusing on a particular aspect of natural language processing, I tried to benefit from the big amount of work that has been already done in Computational Linguistics and Computer Science merging different ideas and techniques. In the first part of the dissertation I explore the universe of Language Engineering in order to clarify how my contribution can be situated. After a survey on the state of the art on robust methods in analysis of natural language data, I focus on the role that Computational Logic plays in relating the syntactic and semantic analysis of natural language to its practical understanding within specific applications. Robustness is considered from two complementary perspectives, borrowing the terminology from modern software engineering: robustness "in the small" and robustness "in the large". The first perspective is discussed while presenting an application for the Interaction through Speech with Information Systems, where robust semantic parsing is used to extract queries from spoken natural language utterances.The second perspective is examplified by the re-engineering of an existing text analysis system using a new Language Engineering methodology: Agent-Oriented Language Engineering. In the second part of the thesis I discuss how cognitive aspects can be integrated into a Language Engineering environment leading to the notion of Cognitive Language Enginering. I tackle the difficult problem of robust dialogue management from both a cognitive and computational perspective. I propose two frameworks for the semantic representation and assimilation of information into the dialogue information state. The first framework allows us to represent and reason about the dynamic aspects of objects and events. The second framework is centered on the notion of mental space and it is used to build representations of the cognitive processing of information during communication.

EPFL2002

Cognitive language engineering towards robust human-computer interaction

Vincenzo Pallotta

EPFL2002