This document discusses developments in text analytics from 2011-2012. It covers major acquisitions in the field, the rise of big data and APIs/platforms, and progress on tasks like information extraction, knowledge integration, and semantic search. It also outlines future directions, including sentiment analysis beyond polarity, identity resolution, speech analytics, and augmented reality interfaces. The overall focus is on generating signals from text to power applications and provide richer information and experiences.

1. Text and Beyond
Seth Grimes
@sethgrimes
#TAS12

2. A slide from the past…

3. Vox Populi

4. Milestones [and goal(s)?] (circa 2011)
Language+ understanding.
• Text, speech, and video.
• Narrative, discourse, and argument.
Information extraction.
Knowledge structuring and integration.
Inference; synthesis.
Language generation.
Conversation; interaction; autonomy.
≈> Convergence, a.k.a. Singularity

5. Text stories of the last 12 months…
Big Data: the 3 Vs.
APIs, platforms, and cloud services.
Acquisitions: Information access.
• Autonomy  HP.
• Endeca  Oracle.
• ISYS  Lexmark.
• Vivisimo  IBM.
Social media magic (?), e.g.,
• Oracle Social Network (+ Collective Intellect).
• SAP Social Media Analytics.
Knowledge, enrichment & integration.

6. Velocity & Volume. (Where’s Variety?)
Filtering
More
Down with IT!
Up with users!

7. A Big Data analytics architecture
(HPCC’s)
http://hpccsystems.com/
http://www.geeklawblog.com/2011/12/lexis-advance-platform-launch-two.html

8. You can’t have it all?!
Where are the
flexibility, the
(data/content)
sophistication,
and real-
timedness?

9. Platform plays; advantage APIs

10. Text stories of the last 12 months…
Big Data: the 3 Vs.
APIs, platforms, and cloud services.
We’re
Acquisitions: Information access. here
• Autonomy  HP.
• Endeca  Oracle.
• ISYS  Lexmark.
• Vivisimo  IBM.
Social media magic (?), e.g.,
• Oracle Social Network (+ Collective Intellect).
• SAP Social Media Analytics.
Knowledge, enrichment & integration.

11. Fusions

12. Social media magic (?) (2 examples)
 “By NetBase”?!
No analytics? 

13. Knowledge, enrichment & integration
Semantics enables join across types and/or sources
and/or structures, using meaningful identifiers, to
create an ensemble that is greater than the sum of
the parts.
Interrelate information to represent knowledge.
Enrichment and integration involve:
• Mappings and transformations.
• Aggregation and collection.
• All the typical data concerns: cleansing, profiling,
consistency, security,…

14. Question Authority
https://secure.wikimedia.org/wiki
pedia/en/wiki/File:Watson_Jeopar
dy.jpg

15. The Semantic Web?
A knowledge representation built on an assemblage of
standards, protocols, and functions.
http://www.cambridgesemantics.com/
semantic-university/semantic-search-
and-the-semantic-web
http://img.freebase.com/api/trans/raw/m/02dtnzv

16. A Semanticized Web
Google
Knowledge
Graph

17. Text+ technology mashups
Text analytics generates semantics to bridge search, BI,
and applications, enabling next-generation
information systems.
Semantic search Information access
(search + text) (search + text + BI)
Search based Search BI
applications
Integrated analytics
(search + text +
(text + BI)
apps)
Applica-
Text analytics tions NextGen CRM, EFM,
(inner circle) MR, marketing, …

18. Milestones [and goal(s)?] re-viewed
✔ Language+ understanding.
~ Text, speech, and video.
✖ Narrative, discourse, and argument.
✔ Information extraction.
✔ Knowledge structuring and integration.
? Inference; synthesis.
~ Language generation.
Conversation; interaction; autonomy.
≈> Convergence, a.k.a. Singularity

19. Personal. Mobile. Intelligent?
http://timoelliott.com/blog/2010/10/sap-businessobjects-augmented-
explorer-now-available-resources-to-test-it.html

20. Text tech initiatives (2011 2012)
Now and near future.
• Beyond-polarity sentiment analysis.
Emotions, intent signals. etc.
• Identity resolution & profile extraction.
Online-social-enterprise data integration.
• Semantic data integration, Complex Data.
• Speech analytics.
• Discourse analysis.
Because isolated messages are not conversations.
• Rich-media content analytics.
• Augmented reality; new human-computer interfaces.

21. A focus on information & applications
Now and near future.
• Signal detection.
Sentiment, emotion, identity, intent.
• Semanticized applications.
Experience/satisfaction sentiment polarity
Linkable, mashable, enrichable.
Positive
• Rich information.
Overall experience / Neutral
Context sensitive, situational. satisfaction
80% Negative
Σ = Sense-making... 60%
40%
Availability of professional Ability to solve business
services / support 20% problems
… but there’s work to do: 0%
Solution / technology Solution / technology ease of
performance use

22. Next year’s talk? --
Text Analytics 
From Sources to Signals to Sense
Seth Grimes
@sethgrimes