MixedEmotions. Social Semantic Emotion Analysis for Innovative Multilingual Big Data Analytics Markets
Proposed start date
2015-04-01
Proposed end date
2017-04-30
Description
MixedEmotions (Grant Agreement no: 141111) will develop innovative multilingual multi-modal Big Data analytics applications that will analyze a more complete emotional profile of user behavior using data from mixed input channels: multilingual text data sources, A/V signal input (multilingual speech, audio, video), social media (social network, comments), and structured data. Commercial applications (implemented as pilot projects) will be in Social TV, Brand Reputation Management and Call Centre Operations. Making sense of accumulated user interaction from different data sources, modalities and languages is challenging and has not yet been explored in fullness in an industrial context.
Publications
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J. Fernando Sánchez-Rada, Carlos A. Iglesias, Hesam Sagha, Björn Schuller, Ian Wood & Paul Buitelaar (2017). Multimodal Multimodel Emotion Analysis as Linked Data. In Proceedings of ACII 2017. San Antonio, Texas, USA.
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Ganggao Zhu & Carlos A. Iglesias. (2017). Computing Semantic Similarity of Concepts in Knowledge Graphs. Transactions on Knowledge and Data Engineering, 29 (1), 72-85.
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J. Fernando Sánchez-Rada, Björn Schuller, Viviana Patti, Paul Buitelaar, Gabriela Vulcu, Felix Bulkhardt et al (2016). Towards a Common Linked Data Model for Sentiment and Emotion Analysis. In J. Fernando Sánchez-Rada & Björn Schuller (editors), Proceedings of the LREC 2016 Workshop Emotion and Sentiment Analysis (ESA 2016), pages 48-54.
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Constantino Román-Gómez. (2015). Development of a Named Entity Recognition System based on Ensemble Machine Learning Algorithms. Final Career Project (TFG). ETSI Telecomunicación, Universidad Politécnica de Madrid.