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María González García (Projects)

The recent massive growth in online media and the rise of user-authored content (e.g weblogs, Twitter, Facebook) has lead to challenges of how to access and interpret these strongly multilingual data, in a timely, efficient, and affordable manner. Scientifically, streaming online media pose new challenges, due to their shorter, noisier, and more colloquial nature. Moreover, they form a temporal stream strongly grounded in events and context. Consequently, existing language technologies fall short onaccuracy, scalability and portability. The goal of this project is to deliver. innovative, portable open-source real-time methods for cross-lingual mining and summarisation of large-scale stream media. TrendMiner will achieve this through an inter-disciplinary approach, combining deep linguistic methods from text processing, knowledge-based reasoning from web science, machine learning, economics, and political science. No expensive human annotated data will be required due to our use of time-series data (e.g. financial markets, political polls) as a proxy. A key novelty will be weakly supervised machine learning algorithms for automatic discovery of new trends and correlations. Scalability and affordability will be addressed through a cloud-based infrastructure for real-time text mining from stream media. Results will be validated in two high-profile case studies: financial decision support (with analysts, traders, regulators, and economists) and political analysis and monitoring (with politicians, economists, and political journalists). The techniques will be generic with many business applications: business intelligence, customer relations management, community support. The project will also benefit society and ordinary citizens by enabling enhanced access to government data archives, summarisation of online health information, and tracking of hot societal issues.

  • Reference: FP7-ICT 287863
  • Financing: European Commission
  • Project type: Público
  • State: Activo
  • Principal investigator: Paloma Martínez Fernández
  • Other investigator: Paloma Martínez Fernández, Lourdes Moreno, Isabel Segura Bedmar, Julián Moreno Schneider, María González García, María Herrero Zazo, Ricardo Revert Arenaz
  • Duration: -
  • https://cordis.europa.eu/project/id/287863

MAVIR is a research network co-funded by the Regional Government of Madrid and the European Social Fund under MA2VICMR (2010-2013) and MAVIR (2006-2009) programs. The core of the consortium consists seven research groups from universities and organisations from the Region of Madrid, namely: namely: •Laboratorio de Cibermetría (CybermetricsLab-CSIC) •Human Language Technologies & Information Retrieval (HLT&IR-UAM) •Laboratorio de Bases de Datos Avanzadas (LABDA-UC3M) •Grupo de Sistemas Inteligentes (GSI-UEM) •Natural Language Processing and Information Retrieval Group (NLP&IR-UNED) •Tecnologías de Audio, Habla y Lenguaje Natural en Sistemas Inteligentes (THALES-UPM) •Grupo de Algorítmica aplicada a la Visión Artificial y la Biometría (GAVAB-URJC)

  • Reference: S2009/TIC-1542
  • Financing:
  • Project type: Público
  • State: Activo
  • Principal investigator: Paloma Martínez Fernández
  • Other investigator: Paloma Martínez Fernández, María González García, María Herrero Zazo
  • Duration: -
  • http://www.mavir.net
  • Reference: CEN-20091026
  • Financing: DAEDALUS S.A dentro del SUBPROGRAMA DE APOYO A CONSORCIOS ESTRATÉGICOS NACIONALES DE INVESTIGACIÓN TÉCNICA (CENIT-E), CEN-20091026
  • Project type: Público
  • State: Activo
  • Principal investigator: Paloma Martínez Fernández
  • Other investigator: Paloma Martínez Fernández, Dolores Cuadra Fernández, Lourdes Moreno, Elena Castro Galán, Ana M. Iglesias Maqueda, Francisco Javier Calle Gómez, Harith Al-Jumaily, César De Pablo Sánchez, Isabel Segura Bedmar, María Teresa Vicente-Díez, David del Valle Agudo, José Luis Martínez Fernández, Jesica Rivero Espinosa, Daniel Sánchez Cisneros, María González García, María Herrero Zazo
  • Duration: -
  • http://www.cenitbuscamedia.es

The main goal of the project is the design and development of a system, which implements a process of automatic generation of subtitles for prerecorded video or audio accompanied by an accurate transcription (screenplay). In this project wants develop a prototype. It will be a tool that will offer support for subtitling of audiovisual content in recorded (movies, documentaries, series, etc…) for different media way such as television, Internet and mobile devices. In this context, the process is called recorded subtitling (off-line or canned) because is not processed in real time; it is treated previously without anytime limits. This automatic support provide a synchronization process of the screenplay with audio by adding time stamps, analyze of errors resulted in the process, and the text subtitles segmentation conform to current standards.

  • Reference: Proyecto Avanza - TSI-020100-2010-184
  • Financing: Ministerio de Industria, Turismo y Comercio (proyecto AVANZA)
  • Project type: Público
  • State: Activo
  • Principal investigator: Lourdes Moreno
  • Other investigator: Paloma Martínez Fernández, Lourdes Moreno, Ana M. Iglesias Maqueda, José Luis Martínez Fernández, Belén Ruiz-Mezcua, María González García
  • Duration: -
  • http://labda.inf.uc3m.es/sagas