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Mostrando ítems 1-10 de 10
Artículo
TAPON: a two-phase machine learning approach for semantic labelling
(Elsevier, 2019-01-01)
Through semantic labelling we enrich structured information from sources such as HTML pages, tables, or JSON files, with labels to integrate it into a local ontology. This process involves measuring some features of the ...
Artículo
TAPON-MT: a versatile framework for semantic labelling
(Elsevier, 2019-07)
Semantic labelling refers to the problem of assigning known labels to the elements of structured information from a source such as an HTML table or an RDF dump with unknown semantics. In the recent years it has become ...
Artículo
Detecting Flight Trajectory Anomalies and Predicting Diversions in Freight Transportation
(Elsevier, 2016)
Timely identifying flight diversions is a crucial aspect of efficient multi-modal transportation. When an airplane diverts, logistics providers must promptly adapt their transportation plans in order to ensure proper ...
Artículo
La Combinación de Sistemas y el PLN
(Sociedad Española para el Procesamiento del Lenguaje Natural (SEPLN), 2010)
La combinación de sistemas constituye un área de investigación ampliamente estudiada en el ámbito del Reconocimiento de Patrones, en donde se han desarrollado múltiples técnicas para aprovechar la diversidad de métodos de ...
Artículo
MCFS: Min-cut-based feature-selection
(Elsevier, 2020)
In this paper, MCFS (Min-Cut-based feature-selection) is presented, which is a feature-selection algorithm based on the representation of the features in a dataset by means of a directed graph. The main contribution of our ...
Artículo
Deep Learning Techniques to Improve the Performance of Olive Oil Classification
(Frontiers Editorial, 2020)
The olive oil assessment involves the use of a standardized sensory analysis according to the “panel test” method. However, there is an important interest to design novel strategies based on the use of Gas Chromatography ...
Artículo
A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables
(Elsevier, 2015)
Light Detection and Ranging (LiDAR) is a remote sensor able to extract three-dimensional information. Environmental models in forest areas have been benefited by the use of LiDAR-derived information in the last years. A ...
Artículo
An evolutionary-weighted majority voting and support vector machines applied to contextual classification of LiDAR and imagery data fusion
(Elsevier, 2015)
Data classification is a critical step to convert remotely sensed data into thematic information. Environmental researchers have recently maximized the synergy between passive sensors and LiDAR (Light Detection and Ranging) ...
Artículo
Trip destination prediction based on past GPS log using a Hidden Markov Model
(Elsevier, 2010)
In this paper, a system based on the generation of a Hidden Markov Model from the past GPS log and cur- rent location is presented to predict a user’s destination when beginning a new trip. This approach dras- tically ...
Artículo
LEAPME: Learning-based Property Matching with Embeddings
(Cornell University, 2020)
Data integration tasks such as the creation and extension of knowledge graphs involve the fusion of heterogeneous entities from many sources. Matching and fusion of such entities require to also match and combine their ...