15,372 research outputs found
Automatic Taxonomy Generation - A Use-Case in the Legal Domain
A key challenge in the legal domain is the adaptation and representation of
the legal knowledge expressed through texts, in order for legal practitioners
and researchers to access this information easier and faster to help with
compliance related issues. One way to approach this goal is in the form of a
taxonomy of legal concepts. While this task usually requires a manual
construction of terms and their relations by domain experts, this paper
describes a methodology to automatically generate a taxonomy of legal noun
concepts. We apply and compare two approaches on a corpus consisting of
statutory instruments for UK, Wales, Scotland and Northern Ireland laws.Comment: 9 page
Semantic HMC for Big Data Analysis
Analyzing Big Data can help corporations to im-prove their efficiency. In
this work we present a new vision to derive Value from Big Data using a
Semantic Hierarchical Multi-label Classification called Semantic HMC based in a
non-supervised Ontology learning process. We also proposea Semantic HMC
process, using scalable Machine-Learning techniques and Rule-based reasoning
Decoding the urban grid: or why cities are neither trees nor perfect grids
In a previous paper (Figueiredo and Amorim, 2005), we introduced the continuity
lines, a compressed description that encapsulates topological and geometrical
properties of urban grids. In this paper, we applied this technique to a large
database of maps that included cities of 22 countries. We explore how this
representation encodes into networks universal features of urban grids and, at the
same time, retrieves differences that reflect classes of cities. Then, we propose an
emergent taxonomy for urban grids
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