Publications related to Structure mining

Validating functional redundancy with mixed generative adversarial networks

Thanh Trung Huynh, Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Trung-Dung Hoang

Data redundancy has been one of the most important problems in data-intensive applications such as data mining and machine learning. Removing data redundancy brings many benefits in efficient data updating, effective data storage, and error-free query proc ...

ELSEVIER2023

Tracing Embodied Narratives of Critical Thinking

Aditi Kothiyal, Shitanshu Mishra

Critical Thinking (CrT) is generally characterized as an abstract thinking process, detached from the (bodily) actions one engages in during the process. Though recent cognitive theories assert that all thinking is action-based, the embodied and distribute ...

SPRINGER INTERNATIONAL PUBLISHING AG2021

Systematic Method for the Energy-Saving Potential Calculation of Air Conditioning Systems via Data Mining. Part II: A Detailed Case Study

Shen Yang, Xianlin Wang

Increased data monitoring enables the energy-efficient operation of air-conditioning systems via data-mining. The latter is projected to have lesser consumption but more comprehensive diagnosis than traditional methods. Following the companion paper that p ...

2021

Data mining in the context of urban metabolism: A case study of Geneva and Lausanne, Switzerland

Claudia Rebeca Binder Signer, Aristide Henri Roger Athanassiadis, Nicole Sophie Wiedmann

The highest share of the global population lives in cities. The current configuration of the latter requires considerable amounts of resource flows causing the degradation of local and global ecosystems. To face the complexity of these challenges, scientis ...

IOP PUBLISHING LTD2021

Systematic Method for the Energy-Saving Potential Calculation of Air-Conditioning Systems via Data Mining. Part I: Methodology

Shen Yang, Xianlin Wang

Air-conditioning systems contribute the most to energy consumption among building equipment. Hence, energy saving for air-conditioning systems would be the essence of reducing building energy consumption. The conventional energy-saving diagnosis method thr ...

2021

Overview of CLEF HIPE 2020: Named Entity Recognition and Linking on Historical Newspapers

Maud Ehrmann, Matteo Romanello

This paper presents an overview of the first edition of HIPE (Identifying Historical People, Places and other Entities), a pioneering shared task dedicated to the evaluation of named entity processing on historical newspapers in French, German and English. ...

Springer2020

Extended Overview of CLEF HIPE 2020: Named Entity Processing on Historical Newspapers

Maud Ehrmann, Matteo Romanello

This paper presents an extended overview of the first edition of HIPE (Identifying Historical People, Places and other Entities), a pioneering shared task dedicated to the evaluation of named entity processing on historical newspapers in French, German and ...

CEUR-WS2020

Nowcasting lightning occurrence from commonly available meteorological parameters using machine learning techniques

Farhad Rachidi-Haeri, Marcos Rubinstein, Amirhossein Mostajabi

Article Open Access Published: 08 November 2019 Nowcasting lightning occurrence from commonly available meteorological parameters using machine learning techniques Amirhossein Mostajabi, Declan L. Finney, Marcos Rubinstein & Farhad Rachidi npj Climate and ...

2019

A semantic-driven approach for Industry 4.0

Dimitrios Kyritsis, Gökan May, Sangje Cho

Toward industry 4.0, modern manufacturing companies are aiming at building digital twins to manage physical assets, processes, people, and places. Since in this environment, massive amounts of data have been generated and collected, integration and managem ...

IEEE2019

A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience

Christian O'Reilly, Elisabetta Iavarone

The curation of neuroscience entities is crucial to ongoing efforts in neuroinformatics and computational neuroscience, such as those being deployed in the context of continuing large-scale brain modelling projects. However, manually sifting through thousa ...

Springer2019

Advancing climate science with knowledge-discovery through data mining

Athanasios Nenes

Global climate change represents one of the greatest challenges facing society and ecosystems today. It impacts key aspects of everyday life and disrupts ecosystem integrity and function. The exponential growth of climate data combined with Knowledge-Disco ...

2018

Mapping affinities: visualizing academic practice through collaboration

Dario Rodighiero

Academic affinities are one of the most fundamental hidden dynamics that drive scientific development. Some affinities are actual, and consequently can be measured through classical academic metrics such as co-authoring. Other affinities are potential, and ...

EPFL2018

Mapping Affinities in Academic Organizations

Frédéric Kaplan, Dario Rodighiero, Boris Beaude

Scholarly affinities are one of the most fundamental hidden dynamics that drive scientific development. Some affinities are actual, and consequently can be measured through classical academic metrics such as co-authoring. Other affinities are potential, an ...

2018

Gaia Data Release 2 Summary of the variability processing and analysis results

Stephan Morgenthaler, Lorenzo Diana, Mária Süveges

Context. The Gaia Data Release 2 (DR2) contains more than half a million sources that are identified as variable stars. ...

EDP SCIENCES S A2018

Discovering Interaction Patterns in Online Learning Environments : A Learning Analytics Research

Mina Shirvani Boroujeni

The increasing amount of data collected in online learning environments provides unique opportunities to better understand the learning processes in different educational settings. Learning analytics research aims at understanding and optimizing learning a ...

EPFL2018

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

Computational development of the nanoporous materials genome

Berend Smit, Peter George Boyd, Yongjin Lee

There is currently a push towards big data and data mining in materials research to accelerate discovery. Zeolites, metal-organic frameworks and other related crystalline porous materials are not immune to this phenomenon, as evidenced by the proliferation ...

Nature Publishing Group2017

A roadmap for the development of precision medicine

Marie-Valentine Renée Agnès Florin, Gérard Escher

The purpose of the roadmap proposed by IRGC is to recommend a structured process that organisations can follow in their transition towards the development of precision medicine. The process is adaptable, and each organisation should further develop it to a ...

International Risk Governance Center (IRGC)2017

Graph learning under sparsity priors

Pascal Frossard, Ntorina Thanou, Hermina Petric Maretic

Graph signals offer a very generic and natural representation for data that lives on networks or irregular structures. The actual data structure is however often unknown a priori but can sometimes be estimated from the knowledge of the application domain. ...

Ieee2017

Interactive Programming by Example

Mikaël Mayer

As of today, programming has never been so accessible. Yet, it remains a challenge for end-users: students, non-technical employees, experts in their domains outside of computer science, and so on. With its forecast potential for solving problems by only o ...

EPFL2017