Sentic computing for patient centric applications

Cambria, Eric and Hussain, Amir and Durrani, Tariq and Havasi, C and Eckl, C and Munro, J; (2010) Sentic computing for patient centric applications. In: 2010 IEEE 10th international conference on signal processing (ICSP). IEEE, CHN, pp. 1279-1282. ISBN 9781424458974 (https://doi.org/10.1109/ICOSP.2010.5657072)

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Abstract

Next-generation patients are far from being peripheral to health-care. They are central to understanding the effectiveness and efficiency of services and how they can be improved. Today a lot of patients are used to reviewing local health services on-line but this social information is just stored in natural language text and it is not machine-accessible and machine-processable. To distil knowledge from this extremely unstructured information we use Sentic Computing, a new opinion mining and sentiment analysis paradigm which exploits AI and Semantic Web techniques to better recognize, interpret and process opinions and sentiments in natural language text. In particular, we use a language visualization and analysis system, a novel emotion categorization model, a resource for opinion mining based on a web ontology and novel techniques for finding and defining topic dependent concepts, namely spectral association and CF-IOF weighting respectively.

  • Item type:Book Section
    ID code:42789
    Dates:
    Date
    Event
    October 2010
    Published
    Notes:[1] BBC–Panorama investigation: Trust Us, We’re an NHS Hospital – http://news.bbc.co.uk/2/hi/uk news/8551668.stm [2] E. Cambria, A. Hussain, C. Havasi, and C. Eckl. Sentic Computing: Exploitation of Common Sense for the Development of Emotion-Sensitive Systems. LNCS, vol. 5967, pp. 148–156. Springer–Verlag, Berlin Heidelberg (2010) [3] E. Cambria, A. Hussain, C. Havasi, and C. Eckl. AffectiveSpace: Blending Common Sense and Affective Knowledge to Perform Emotive Reasoning. In: WOMSA at CAEPIA09, Seville (2009) [4] C. Strapparava, and A. Valitutti: WordNet-Affect: an Affective Extension of WordNet. In: LREC, Lisbon (2004) [5] C. Havasi, R. Speer, and J. Alonso: ConceptNet 3: a Flexible, Multilingual Semantic Network for Common Sense Knowledge. In: RANLP, Borovets (2007) [6] R. Speer, C. Havasi, and H. Lieberman: AnalogySpace: Reducing the Dimensionality of Common Sense Knowledge. In: AAAI, Chicago (2008) [7] E. Cambria, A. Hussain, C. Havasi, and C. Eckl. Common Sense Computing: From the Society of Mind to Digital Intuition and Beyond. LNCS, vol. 5707, pp. 252–259. Springer–Verlag, Berlin Heidelberg (2009) [8] R. Plutchik. The Nature of Emotions. American Scientist 89(4), 344–350 (2001) [9] M. Minsky. The Emotion Machine. Simon and Schuster, New York (2006) [10] E. Cambria, R. Speer, C. Havasi, and A. Hussain. SenticNet: a Publicly Available Semantic Resource for Opinion Mining. In: AAAI CSK10, Arlington (2010) [11] C. Havasi, R. Speer, and J. Holmgren. Automated Color Selection Using Semantic Knowledge. In: AAAI CSK10, Arlington (2010) [12] E. Cambria, A. Hussain, C. Havasi, C. Eckl and J. Munro: Towards Crowd Validation of the UK National Health Service. In: WebSci10, Raleigh (2010) [13] Patient Opinion – http://www.patientopinion.org.uk [14] NHS Choices – http://www.nhs.uk
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:08 Feb 2013 14:53
    Last modified:11 Nov 2024 14:51
    URI:https://strathprints.strath.ac.uk/id/eprint/42789
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