Concept

Extraction de connaissances

Publications associées (159)

Ontology for SEAM Service Models

Alain Wegmann, Gorica Tapandjieva Sekulovska

A service system is a popular concept in academia and industry. At the same time, it is a challenging concept to represent, due to its recursive nature and difficulty to relate it to entities in reality. In this paper we present an ontology for modeling se ...

2018

Semantic Interoperability and Open IoT APIs for Smart Cities Applications

Prodromos Kolyvakis

As the percentage of the total population living in urban regions is increasing, new challenges for the cities of the future arise. Smart Cities emerged as a solution to these challenges building on the strength of intelligent information, communication te ...

SPRINGER-VERLAG BERLIN2018

Skill Modelling for Digital Factories

Damiano Nunzio Arena

In the past two decades, the use of ontologies has been proven to be an effective tool for enriching existing information systems in the digital data modelling domain and exploiting those assets for semantic interoperability. Despite the presence of many d ...

SPRINGER-VERLAG BERLIN2018

Automated Taxonomy Induction and its Applications

Amit Gupta

Machine-readable semantic knowledge in the form of taxonomies (i.e., a collection of is-a edges) has proved to be beneficial in an array of NLP tasks including inference, textual entailment, question answering and information extraction. Such widespread ut ...

EPFL2017

Dataset Construction via Attention for Aspect Term Extraction with Distant Supervision

Athanasios Giannakopoulos, Claudiu-Cristian Musat, Diego Matteo Antognini

Aspect Term Extraction (ATE) detects opinionated aspect terms in sentences or text spans, with the end goal of performing aspect-based sentiment analysis. The small amount of available datasets for supervised ATE and the fact that they cover only a few dom ...

2017

Efficient Document Filtering Using Vector Space Topic Expansion and Pattern-Mining: The Case of Event Detection in Microposts

Karl Aberer, Philippe Cudré-Mauroux, Julia Proskurnia, Carlos Castillo

Automatically extracting information from social media is challenging given that social content is often noisy, ambiguous, and inconsistent. However, as many stories break on social channels first before being picked up by mainstream media, developing meth ...

2017

Semi-supervised Learning with Semantic Knowledge Extraction for Improved Speech Recognition in Air Traffic Control

Petr Motlicek

Automatic Speech Recognition (ASR) can introduce higher levels of automation into Air Traffic Control (ATC), where spoken language is still the predominant form of communication. While ATC uses standard phraseology and a limited vocabulary, we need to adap ...

2017

Semi-supervised Learning with Semantic Knowledge Extraction for Improved Speech Recognition in Air Traffic Control

Petr Motlicek

Idiap2017

Towards Producing Human-Validated Translation Resources for the Fula language through WordNet Linking

Martin Benjamin, Khalil Mrini

We propose methods to link automatically parsed linguistic data to the WordNet. We apply these methods on a trilingual dictionary in Fula, English and French. Dictionary entry parsing is used to collect the linguistic data. Then we connect it to the Open M ...

ACL Anthology2017

Evaluating Attention Networks for Anaphora Resolution

Andrei Popescu-Belis, Nikolaos Pappas, Lesly Sadiht Miculicich Werlen

In this paper, we evaluate the results of using inter and intra attention mechanisms from two architectures, a Deep Attention Long Short-Term Memory-Network (LSTM-N) (Cheng et al., 2016) and a Decomposable Attention model (Parikh et al., 2016), for anaphor ...

Idiap2017

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