Sentic computing for patient centric applications

Eric Cambria, Amir Hussain, Tariq Durrani, C Havasi, C Eckl, J Munro

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

48 Citations (Scopus)

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.
LanguageEnglish
Title of host publication2010 IEEE 10th international conference on signal processing (ICSP)
Place of PublicationNew York
PublisherIEEE
Pages1279-1282
Number of pages4
ISBN (Print)9781424458974
DOIs
Publication statusPublished - Oct 2010
Event10th IEEE International Conference on Signal Processing - Beijing, China
Duration: 24 Oct 201028 Oct 2010

Conference

Conference10th IEEE International Conference on Signal Processing
CountryChina
CityBeijing
Period24/10/1028/10/10

Fingerprint

Information use
Semantic Web
Health care
Ontology
Visualization
Health

Keywords

  • sentic computing
  • patient centric applications
  • semantics
  • XML
  • analytical models
  • approximation methods
  • databases
  • hospitals
  • natural languages

Cite this

Cambria, E., Hussain, A., Durrani, T., Havasi, C., Eckl, C., & Munro, J. (2010). Sentic computing for patient centric applications. In 2010 IEEE 10th international conference on signal processing (ICSP) (pp. 1279-1282). New York: IEEE. https://doi.org/10.1109/ICOSP.2010.5657072
Cambria, Eric ; Hussain, Amir ; Durrani, Tariq ; Havasi, C ; Eckl, C ; Munro, J. / Sentic computing for patient centric applications. 2010 IEEE 10th international conference on signal processing (ICSP) . New York : IEEE, 2010. pp. 1279-1282
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note = "[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",
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Cambria, E, Hussain, A, Durrani, T, Havasi, C, Eckl, C & Munro, J 2010, Sentic computing for patient centric applications. in 2010 IEEE 10th international conference on signal processing (ICSP) . IEEE, New York, pp. 1279-1282, 10th IEEE International Conference on Signal Processing, Beijing, China, 24/10/10. https://doi.org/10.1109/ICOSP.2010.5657072

Sentic computing for patient centric applications. / Cambria, Eric ; Hussain, Amir; Durrani, Tariq; Havasi, C; Eckl, C; Munro, J.

2010 IEEE 10th international conference on signal processing (ICSP) . New York : IEEE, 2010. p. 1279-1282.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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KW - semantics

KW - XML

KW - analytical models

KW - approximation methods

KW - databases

KW - hospitals

KW - natural languages

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Cambria E, Hussain A, Durrani T, Havasi C, Eckl C, Munro J. Sentic computing for patient centric applications. In 2010 IEEE 10th international conference on signal processing (ICSP) . New York: IEEE. 2010. p. 1279-1282 https://doi.org/10.1109/ICOSP.2010.5657072