Guillermo Álvaro Rey, Carmen Córdoba, Víctor Penela,
Michelangelo Castagnone, Francesco Carbone, José Manuel
Gómez-Pérez, ...
Microblogging?
Not this
http://www.flickr.com/photos/bloggingdagger/
“There is a revolution
coming for knowledge
workers”
Tim O’Reilly
referring to Twitter
(2009)
But …
… we already
have an
almighty
KM System
K.I.S.S.
Keep It Simple, Stupid Son
K.I.S.S.
Users care about results
not about complexity
K.I.S.S.
Users want to find
not to search
K.I.S.S.
the user to the system
the system to the user
Adapt:
How does
it work?
http://www.flickr.com/photos/17258892@N05
Message Indexing
Expert Indexing
Message Search
Expert Search
Linked Data
Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/
Context
Context data
Implementation:
miKrow architecture
miKrow
architecture,
extended
Demo
Evaluation
In-house testing
Evaluation
1: Cold start problem
 Feed the system with
previous existing knowledge
Evaluation
2: Semantic suggestions
were better perceived
 Highlight them
Evaluation
3: Some stop words
were not identified
 Dynamically detect new
expressions like “working
on…”, “doing…”
Video
miKrow success story…
http://www.youtube.com/watch?v=pXdGE4Gxu0A
Guillermo Álvaro, Carmen Córdoba, Víctor Penela,
Michelangelo Castagnone, Francesco Carbone,
José Manuel Gómez-Pérez, Jesú...
miKrow: An Intra-Enterprise Semantic Microblogging Tool as a Micro-Knowledge Management Solution
miKrow: An Intra-Enterprise Semantic Microblogging Tool as a Micro-Knowledge Management Solution
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miKrow: An Intra-Enterprise Semantic Microblogging Tool as a Micro-Knowledge Management Solution

  1. 1. Guillermo Álvaro Rey, Carmen Córdoba, Víctor Penela, Michelangelo Castagnone, Francesco Carbone, José Manuel Gómez-Pérez, Jesús Contreras Valencia, 26 October 2010 (KMIS 2010) miKrow: An Intra-Enterprise Semantic Microblogging Tool as a Micro-Knowledge Management Solution
  2. 2. Microblogging?
  3. 3. Not this http://www.flickr.com/photos/bloggingdagger/
  4. 4. “There is a revolution coming for knowledge workers” Tim O’Reilly referring to Twitter (2009)
  5. 5. But …
  6. 6. … we already have an almighty KM System
  7. 7. K.I.S.S. Keep It Simple, Stupid Son
  8. 8. K.I.S.S. Users care about results not about complexity
  9. 9. K.I.S.S. Users want to find not to search
  10. 10. K.I.S.S. the user to the system the system to the user Adapt:
  11. 11. How does it work? http://www.flickr.com/photos/17258892@N05
  12. 12. Message Indexing
  13. 13. Expert Indexing
  14. 14. Message Search
  15. 15. Expert Search
  16. 16. Linked Data Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/
  17. 17. Context Context data
  18. 18. Implementation:
  19. 19. miKrow architecture
  20. 20. miKrow architecture, extended
  21. 21. Demo
  22. 22. Evaluation In-house testing
  23. 23. Evaluation 1: Cold start problem  Feed the system with previous existing knowledge
  24. 24. Evaluation 2: Semantic suggestions were better perceived  Highlight them
  25. 25. Evaluation 3: Some stop words were not identified  Dynamically detect new expressions like “working on…”, “doing…”
  26. 26. Video miKrow success story… http://www.youtube.com/watch?v=pXdGE4Gxu0A
  27. 27. Guillermo Álvaro, Carmen Córdoba, Víctor Penela, Michelangelo Castagnone, Francesco Carbone, José Manuel Gómez-Pérez, Jesús Contreras mikrow@isoco.com http://mikrow.isoco.net/about Thanks!

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