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AUTOMATIC MAPPING OF
MOTIVATIONAL TEXT MESSAGES INTO
ONTOLOGICAL ENTITIES FOR SMART
COACHING APPLICATIONS
C. VILLALONGA(*), H. OP DEN AKKER, H. HERMENS, L.J. HERRERA, H. POMARES, I. ROJAS,
O. VALENZUELA, O. BANOS
(*) claudia.villalonga@unir.net
23/3/18 2
E-COACHING
WHY IS IT THAT CHALLENGING?
 Major efforts have been mainly targeted
at improving the quantification part
(oversimplification vs exaggeration)
 “Generic” motivational messages (one-
size-does-not-fit-all)
 Shallow recommendations (explanation
of goals, how to reach them,
implications, etc.)
 We are still learning…
23/3/18 3
MOTIVATIONAL MESSAGES FOR E-COACHING
MAIN CHALLENGES
 Represent the principal, and perhaps more natural,
means for translating behavioral findings into easy-to-
follow and realizable recommendations (actions)
 KEY challenges:
 Generation of relevant messages tailored to the
performance, needs and characteristics of each
specific user [Noar2007]
 Fostering the diversity of the messages to
increase adherence and make the coaching system
more realistic and trustworthy [opdenAkker2015]
Noar et al. Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions. Psychological bulletin 133, 4 (2007),
673.
op den Akker et al.Tailored motivational message generation: A model and practical framework for real-time physical activity coaching. Journal of
Biomedical Informatics 55 (2015), 104-115.
23/3/18 4
FRAMEWORK OF MOTIVATIONAL MESSAGES
PROPOSED SOLUTION
23/3/18 5
FRAMEWORK OF MOTIVATIONAL MESSAGES
MOTIVATIONAL MESSAGE ONTOLOGY
“You should walk the dog to the park early in the morning”
23/3/18 6
FRAMEWORK OF MOTIVATIONAL MESSAGES
AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES
“You should walk the dog to the park early in the morning”
Automatic Mapping
23/3/18 7
AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES
LINGUISTIC ANALYSIS
“You should walk the dog to the park early in the morning”
predicatesubject
Part of
Speech
pronoun
verb
verb
article
article
article
noun
noun
noun
adverb
preposition
preposition
Grammatical
Structure
object modifiermodifier
23/3/18 8
AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES
LINGUISTIC ANALYSIS
“You should walk the dog to the park early in the morning”
predicatesubject
pronoun
verb
verb
article
article
article
noun
noun
noun
adverb
preposition
preposition
object modifiermodifier
ACTION LOCATION TIMEELEMENT
23/3/18 9
AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES
ONTOLOGICAL REPRESENTATION
ACTION PLACE TIMEELEMENT
“You should walk the dog to the park early in the morning”
23/3/18 10
AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES
ONTOLOGICAL REPRESENTATION
“You should walk the dog to the park early in the morning”
TIME
ACTION
ELEMENT
PLACE
23/3/18 11
AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES
MESSAGE SPLITTING
“Walk or run to the park!”
“Walk to the park!” “Run to the park!”
23/3/18 12
AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES
MESSAGE INFERENCE
“Why don’t you go to the gym and practice some exercise?”
“Why don’t you go to the park and practice some exercise?”
Ontology reasoning
23/3/18 13
AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES
IMPLEMENTATION
 Java Implementation
 Stanford CoreNLP
 Apache Jena (v2.11.2)
23/3/18 14
CONCLUSIONS
This work contributes with:
 A new approach for automatically extracting the semantics of motivational
messages and creating the ontological representation of these messages
Future work:
 Evaluation of the message mapping method
 Improvement of the method to infer new messages based on the
knowledge modeled in the ontology
 Extension of the motivational message ontology to include more concepts
by linking available ontologies and thesaurus
 Implementation of the message retrieval method to have a fully functional
framework for the automatic generation of tailored coaching messages
23/3/18 15
Thank you!
Questions?
This project has received funding from the European Union’s Horizon 2020 research
and innovation programme under grant agreement No 769553.

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Automatic mapping of motivational text messages into ontological entities for smart coaching applications

  • 1. AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES INTO ONTOLOGICAL ENTITIES FOR SMART COACHING APPLICATIONS C. VILLALONGA(*), H. OP DEN AKKER, H. HERMENS, L.J. HERRERA, H. POMARES, I. ROJAS, O. VALENZUELA, O. BANOS (*) claudia.villalonga@unir.net
  • 2. 23/3/18 2 E-COACHING WHY IS IT THAT CHALLENGING?  Major efforts have been mainly targeted at improving the quantification part (oversimplification vs exaggeration)  “Generic” motivational messages (one- size-does-not-fit-all)  Shallow recommendations (explanation of goals, how to reach them, implications, etc.)  We are still learning…
  • 3. 23/3/18 3 MOTIVATIONAL MESSAGES FOR E-COACHING MAIN CHALLENGES  Represent the principal, and perhaps more natural, means for translating behavioral findings into easy-to- follow and realizable recommendations (actions)  KEY challenges:  Generation of relevant messages tailored to the performance, needs and characteristics of each specific user [Noar2007]  Fostering the diversity of the messages to increase adherence and make the coaching system more realistic and trustworthy [opdenAkker2015] Noar et al. Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions. Psychological bulletin 133, 4 (2007), 673. op den Akker et al.Tailored motivational message generation: A model and practical framework for real-time physical activity coaching. Journal of Biomedical Informatics 55 (2015), 104-115.
  • 4. 23/3/18 4 FRAMEWORK OF MOTIVATIONAL MESSAGES PROPOSED SOLUTION
  • 5. 23/3/18 5 FRAMEWORK OF MOTIVATIONAL MESSAGES MOTIVATIONAL MESSAGE ONTOLOGY “You should walk the dog to the park early in the morning”
  • 6. 23/3/18 6 FRAMEWORK OF MOTIVATIONAL MESSAGES AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES “You should walk the dog to the park early in the morning” Automatic Mapping
  • 7. 23/3/18 7 AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES LINGUISTIC ANALYSIS “You should walk the dog to the park early in the morning” predicatesubject Part of Speech pronoun verb verb article article article noun noun noun adverb preposition preposition Grammatical Structure object modifiermodifier
  • 8. 23/3/18 8 AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES LINGUISTIC ANALYSIS “You should walk the dog to the park early in the morning” predicatesubject pronoun verb verb article article article noun noun noun adverb preposition preposition object modifiermodifier ACTION LOCATION TIMEELEMENT
  • 9. 23/3/18 9 AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES ONTOLOGICAL REPRESENTATION ACTION PLACE TIMEELEMENT “You should walk the dog to the park early in the morning”
  • 10. 23/3/18 10 AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES ONTOLOGICAL REPRESENTATION “You should walk the dog to the park early in the morning” TIME ACTION ELEMENT PLACE
  • 11. 23/3/18 11 AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES MESSAGE SPLITTING “Walk or run to the park!” “Walk to the park!” “Run to the park!”
  • 12. 23/3/18 12 AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES MESSAGE INFERENCE “Why don’t you go to the gym and practice some exercise?” “Why don’t you go to the park and practice some exercise?” Ontology reasoning
  • 13. 23/3/18 13 AUTOMATIC MAPPING OF MOTIVATIONAL TEXT MESSAGES IMPLEMENTATION  Java Implementation  Stanford CoreNLP  Apache Jena (v2.11.2)
  • 14. 23/3/18 14 CONCLUSIONS This work contributes with:  A new approach for automatically extracting the semantics of motivational messages and creating the ontological representation of these messages Future work:  Evaluation of the message mapping method  Improvement of the method to infer new messages based on the knowledge modeled in the ontology  Extension of the motivational message ontology to include more concepts by linking available ontologies and thesaurus  Implementation of the message retrieval method to have a fully functional framework for the automatic generation of tailored coaching messages
  • 15. 23/3/18 15 Thank you! Questions? This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 769553.

Editor's Notes

  1. temporal modifier