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Findability Strategies for
Crossing the Knowledge
Chasm
INTER-AMERICAN
DEVELOPMENT BANK
Norma Palomino, DPS
npalomino@iadb.org
Chief of Information Services
Knowledge, Innovation and
Communications Sector
Word Vectors
“You shall know a word
by the company it keeps”
John Firth. (1957). Modes of Meaning.
Oxford, UK: Oxford University Press
FINDABILITY VISIBILITY ANTICIPATION
IDB
Sector
Indicators
IDB
Publications
External
Information
Portals
IDB
Datasets
Data Sources
ETL
Automatic Tagging
Knowledge Extraction
Knowledge Base
User Profile Context
External
User
Reccommendation System
Internal
User
THANK YOU!
Image Credits:
• Slide 3 (Pythagoras): PRO News: https://www.pronews.gr/istoria/84901_i-armonia-ton-sfairon-toy-
pythagora-kai-sympan
• Slides 3, 5, 19: Rocher, Richard. (Winter 2017). CS224d: Deep Learning for Natural Language
Processing [course slides]. Stanford, CA: Stanford NLP Group.
• Slide 5 (CBOW vs Skipgram models): Landthaler, Joerg et al. (June 2017). Extending Thesauri Using
Word Embeddings and the Intersection Method. In: Proceedings of the Second Workshop on
Automated Semantic Analysis of Information in Legal Text (ASAIL 2017), June 16, 2017, London, UK.
• Slide 6 (encoder-decoder model for translation): Weng, Lilian. (Jun 24, 2018. Attention? Attention!. In
Lil’Log. https://lilianweng.github.io/lil-log/2018/06/24/attention-attention.html
• Slide 7 (neural networks and predictions):Dalinina, Ruslana (October 10, 2017). Word Embeddings: A
Natural Language Processing Crash Course. In DataScience.com,
https://www.datascience.com/resources/notebooks/word-embeddings-in-python
• Slide 6: numbers and space: https://papers.nips.cc/paper/5021-distributed-representations-of-words-
and-phrases-and-their-compositionality.pdf
• Slide 8: Source: Sutskever, I., Vinyals, O., & Le, Q. V. (2014). Sequence to sequence learning with
neural networks. In Advances in neural information processing systems (pp. 3104-3112).
• Slide 13: IDB Projects website: https://www.iadb.org/en/projects
• Slide 19 (jar image): What Will Fill Your Happiness Jar? - https://pegfitzpatrick.com/. In Pinterest,
https://www.pinterest.com/pin/232779874461685820
• Slide 17: MIT. Norman: Wold’s first psychopath AI: http://norman-ai.mit.edu/#inkblot
• Slide 20: Luong, Thang. (Spring 2016). Neural Machine Translation [slide 54]. In Rocher, Richard.
(Winter 2017). CS224d: Deep Learning for Natural Language Processing [course slides]. Stanford, CA:
Stanford NLP Group.
• Slide 23: IDB Open Data website: https://data.iadb.org/
Norma Palomino, DPS
npalomino@iadb.org
Chief of Information Services
Knowledge, Innovation and
Communications Sector

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KM SHOWCASE 2019 - Findability Strategies

  • 1. Findability Strategies for Crossing the Knowledge Chasm INTER-AMERICAN DEVELOPMENT BANK Norma Palomino, DPS npalomino@iadb.org Chief of Information Services Knowledge, Innovation and Communications Sector
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  • 4. “You shall know a word by the company it keeps” John Firth. (1957). Modes of Meaning. Oxford, UK: Oxford University Press
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  • 11. IDB Sector Indicators IDB Publications External Information Portals IDB Datasets Data Sources ETL Automatic Tagging Knowledge Extraction Knowledge Base User Profile Context External User Reccommendation System Internal User
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  • 25. THANK YOU! Image Credits: • Slide 3 (Pythagoras): PRO News: https://www.pronews.gr/istoria/84901_i-armonia-ton-sfairon-toy- pythagora-kai-sympan • Slides 3, 5, 19: Rocher, Richard. (Winter 2017). CS224d: Deep Learning for Natural Language Processing [course slides]. Stanford, CA: Stanford NLP Group. • Slide 5 (CBOW vs Skipgram models): Landthaler, Joerg et al. (June 2017). Extending Thesauri Using Word Embeddings and the Intersection Method. In: Proceedings of the Second Workshop on Automated Semantic Analysis of Information in Legal Text (ASAIL 2017), June 16, 2017, London, UK. • Slide 6 (encoder-decoder model for translation): Weng, Lilian. (Jun 24, 2018. Attention? Attention!. In Lil’Log. https://lilianweng.github.io/lil-log/2018/06/24/attention-attention.html • Slide 7 (neural networks and predictions):Dalinina, Ruslana (October 10, 2017). Word Embeddings: A Natural Language Processing Crash Course. In DataScience.com, https://www.datascience.com/resources/notebooks/word-embeddings-in-python • Slide 6: numbers and space: https://papers.nips.cc/paper/5021-distributed-representations-of-words- and-phrases-and-their-compositionality.pdf • Slide 8: Source: Sutskever, I., Vinyals, O., & Le, Q. V. (2014). Sequence to sequence learning with neural networks. In Advances in neural information processing systems (pp. 3104-3112). • Slide 13: IDB Projects website: https://www.iadb.org/en/projects • Slide 19 (jar image): What Will Fill Your Happiness Jar? - https://pegfitzpatrick.com/. In Pinterest, https://www.pinterest.com/pin/232779874461685820 • Slide 17: MIT. Norman: Wold’s first psychopath AI: http://norman-ai.mit.edu/#inkblot • Slide 20: Luong, Thang. (Spring 2016). Neural Machine Translation [slide 54]. In Rocher, Richard. (Winter 2017). CS224d: Deep Learning for Natural Language Processing [course slides]. Stanford, CA: Stanford NLP Group. • Slide 23: IDB Open Data website: https://data.iadb.org/ Norma Palomino, DPS npalomino@iadb.org Chief of Information Services Knowledge, Innovation and Communications Sector