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Concept

Annotation

Related publications (24)

Co-encoding embodied knowledge in Southern Chinese martial arts: a collaboration between computists, experts, and digital models

Yumeng Hou

This research, within the framework of computational archives, inspects a novel approach to representing intangible knowledge in traditional martial arts. The methodology presents a unity of ontological modeling, semantic annotation, and feature-based mach ...

Zenodo2023

KNNs of Semantic Encodings for Rating Prediction

Léo Jules Laugier

This paper explores a novel application of textual semantic similarity to user-preference representation for rating prediction. The approach represents a user's preferences as a graph of textual snippets from review text, where the edges are defined by sem ...

IEEE2023

HIPE-2022 Shared Task Named Entity Datasets

Maud Ehrmann, Matteo Romanello

HIPE-2022 datasets used for the HIPE 2022 shared task on named entity recognition and classification (NERC) and entity linking (EL) in multilingual historical documents. HIPE-2022 datasets are based on six primary datasets assembled and prepared for the sh ...

2022

Introducing the HIPE 2022 Shared Task: Named Entity Recognition and Linking in Multilingual Historical Documents

Maud Ehrmann, Matteo Romanello

We present the HIPE-2022 shared task on named entity processing in multilingual historical documents. Following the success of the first CLEF-HIPE-2020 evaluation lab, this edition confronts systems with the challenges of dealing with more languages, learn ...

Springer International Publishing2022

Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation

Jean-Marc Vesin, Etienne Pruvot, Sasan Yazdani, Adrian Luca, Yann Prudat

Background and objective The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time ...

BMC2022

Language Resources for Historical Newspapers: the Impresso Collection

Maud Ehrmann, Matteo Romanello, Raphaël Barman

Following decades of massive digitization, an unprecedented amount of historical document facsimiles can now be retrieved and accessed via cultural heritage online portals. If this represents a huge step forward in terms of preservation and accessibility, ...

European Language Resources Association2020

Multi-scale sequential network for semantic text segmentation and localization

Jean-Marc Odobez, Olivier Canévet, Michael Villamizar

We present a novel method for semantic text document analysis which in addition to localizing text it labels the text in user-defined semantic categories. More precisely, it consists of a fully-convolutional and sequential network that we apply to the part ...

2020

Learning to Reduce Annotation Load

Ksenia Konyushkova

Modern machine learning methods and their applications in computer vision are known to crave for large amounts of training data to reach their full potential. Because training data is mostly obtained through humans who manually label samples, it induces a ...

EPFL2019

Learning Approach to Delineation of Curvilinear Structures in 2D and 3D Images

Agata Justyna Mosinska

Detection of curvilinear structures has long been of interest due to its wide range of applications. Large amounts of imaging data could be readily used in many fields, but it is practically not possible to analyze them manually. Hence, the need for automa ...

EPFL2019

A Framework for Collaborative Curation of Neuroscientific Literature

Sean Lewis Hill, Christian O'Reilly, Elisabetta Iavarone

Large models of complex neuronal circuits require specifying numerous parameters, with values that often need to be extracted from the literature, a tedious and error-prone process. To help establishing shareable curated corpora of annotations, we have dev ...

Frontiers Research Foundation2017

A Method for Record Linkage with Sparse Historical Data

Maud Ehrmann, Giovanni Colavizza, Yannick Rochat

Massive digitization of archival material, coupled with automatic document processing techniques and data visualisation tools offers great opportunities for reconstructing and exploring the past. Unprecedented wealth of historical data (e.g. names of perso ...

2016

Acquiring Broad Commonsense Knowledge for Sentiment Analysis Using Human Computation

Marina Boia

While artificial intelligence is successful in many applications that cover specific domains, for many commonsense problems there is still a large gap with human performance. Automated sentiment analysis is a typical example: while there are techniques tha ...

EPFL2016

Contextualized ranking of entity types based on knowledge graphs

Karl Aberer, Philippe Cudré-Mauroux, Michele Catasta, Roman Prokofyev

A large fraction of online queries targets entities. For this reason, Search Engine Result Pages (SERPs) increasingly contain information about the searched entities such as pictures, short summaries, related entities, and factual information. A key facet ...

Elsevier Science Bv2016

Discourse-level features for statistical machine translation

Thomas Meyer

Machine Translation (MT) has progressed tremendously in the past two decades. The rule-based and interlingua approaches have been superseded by statistical models, which learn the most likely translations from large parallel corpora. System design does not ...

EPFL2015

The Schema Editor of OpenIoT for Semantic Sensor Networks

Jean Paul Calbimonte Perez

Ontologies provide conceptual abstractions over data, in domains such as the Internet of Things, in a way that sensor data can be harvested and interpreted by people and applications. The Semantic Sensor Network (SSN) ontology is the de-facto standard for ...

2015

Rehabilitation of Count-based Models for Word Vector Representations

Rémi Philippe Lebret

Recent works on word representations mostly rely on predictive models. Distributed word representations (aka word embeddings) are trained to optimally predict the contexts in which the corresponding words tend to appear. Such models have succeeded in captu ...

Springer International Publishing2015

Similarity Learning Over Large Collaborative Networks

Majid Yazdani

In this thesis, we propose novel solutions to similarity learning problems on collaborative networks. Similarity learning is essential for modeling and predicting the evolution of collaborative networks. In addition, similarity learning is used to perform ...

EPFL2013

Joint Statistical Analysis of Images and Keywords with Applications in Semantic Image Enhancement

Sabine Süsstrunk, Albrecht Johannes Lindner, Appu Shaji

With the advent of social image-sharing communities, millions of images with associated semantic tags are now available online for free and allow us to exploit this abundant data in new ways. We present a fast non-parametric statistical framework designed ...

2012

SeMiTri: A Framework for Semantic Annotation of Heterogeneous Trajectories

Karl Aberer, Stefano Spaccapietra, Christine Parent, Zhixian Yan, Dipanjan Chakraborty

GPS devices allow recording the movement track of the moving object they are attached to. This data typically consists of a stream of spatio-temporal (x,y,t) points. For application purposes the stream is transformed into finite subsequences called {\em tr ...

ACM2011

Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images

Graham Knott, Marco Cantoni

We describe a protocol for fully automated detection and segmentation of asymmetric, presumed excitatory, synapses in serial electron microscopy images of the adult mammalian cerebral cortex, taken with the focused ion beam, scanning electron microscope (F ...

2011