The Text Analytics Market(s)

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17 Νοε 2013 (πριν από 3 χρόνια και 6 μήνες)

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The Text Analytics Market(s)

Where semantically
-
aware technologies play a role


by

Curt A. Monash, Ph.D.

President, Monash Research

Editor,
Text Technologies

contact@monash.com

http://www.monash.com

http://www.texttechnologies.com

8 linguistics
-
based businesses


Web search


Public
-
facing site search


Enterprise search & knowledge management


Custom publishing


Text mining and extraction


Spam filtering


Voice recognition and NLP


Machine translation

Web search



Giant oligopoly


Startups aren't gaining traction …


… and neither are leaders’ whizz
-
bang features


Three kinds of search


Navigational


Innovation = Maps, part
-
of
-
page smartness


Informational


Innovation is scattershot …


… because people are content with how this works


Transactional


Big bucks


Big adversarial information retrieval problem


Semantics isn’t the issue




Web search vendor issues today



Physical efficiency


Adversarial information retrieval


Monetization


Regulation


Branding …


… none of which are about semantics


Future web search issues



Better popularity metrics


Better use of context (tagging helps)


Geography/geocoding!!


Sub
-
page retrieval (tagging will be huge)


Looking through security barriers


Better UIs (Clusters/facets? Voice?)


Finally a role for sophisticated semantics!


But how good does the technology have to get before
people care?



One
-
size
-
fits
-
all enterprise search failed


Overreaching had a lot to do with that



E
-
commerce search isn't general search


Text mining isn't search (or clustering)


Custom publishing isn't exactly search


Public
-
facing site search



It has dual goals


What the user actually wants


What you want the user to see


E
-
commerce and general search are separate
businesses


E
-
commerce = province of smaller vendors


General = province of search, portal, or CMS vendors


Hand
-
tagging is key …


… or else generic Google is usually superior


Role of sophisticated semantics starts and usually
ends w/ hand tagging


Many reasons to buy true enterprise search



General productivity


Sure beats looking through file cabinets


“Wouldn't it be nice if ...”


KM dreams


Compliance


“Thou shalt …


Search specialized external databases


Medline


News/National intelligence


Taxonomies and RDF both play well here


Bollixed enterprise search market landscape



Multiple generations of vendors flamed out


Verity


Excalibur (endlessly backed by Allen & Company)


Fulcrum et al.


FAST


Market dynamics are screwy


Google has brand name, ease of installation


Microsoft, Oracle, SAP, and Autonomy are all confused


Small vendors are ... small


Products are sold for inappropriate apps


Compliance is driving demand


Facets and clusters are popular





Kinds of enterprise search



Find a specific document


Find an answer


Find ALL documents


Find an expert


Semantic technologies could help with all of those


Technical challenges in enterprise search



Documents may not exist


Many formats


Corpus weighting


No good popularity metrics


Security


Ease of adoption


The problem isn’t
just

insufficiently good semantics

Custom publishing



More precise than search


Sophisticated extraction


Focus on document
parts


Started with technical publishers (and intelligence)


Expanded to


Other technical documents


Other publishers


Semantics is central to this market


This is one of the top application areas for extraction


Text mining



Really about sophisticated extraction


Apps and verticals mirror data mining


The action is in sentiment analysis ...


... and ease of use


Otherwise the industry seems tired



The original text mining apps: Early warning

Source: July, 2006 post on
Text Technologies



Vehicle safety


Other manufacturing/warranty analysis apps


Reputation management


Other customer sentiment apps


Anti
-
terrorism


Sarbanes
-
Oxley compliance


(continued …)

More early warning

(… continued)



Antifraud


Stopping money laundering


Clinical applications (some)


Early insurance risk management apps


Early experimental hedge fund apps


Employee (dis)satisfaction (missing from the
original list)


Customer/market intelligence


Now drive text mining growth


Internal Voice of the Customer came first


Voice of the Market has blended in


Sales, buying, and delivery practices are in line


Departmental buying


SaaS delivery


Many vendors focus(ing) on this segment:


Attensity


Clarabridge


SAS


SPSS


Expert System S.p.A



Three ways to use text mining/extraction


Business intelligence


Reports, dashboards


Attensity, Clarabridge


Predictive analytics


Data mining


SAS, SPSS


Custom publishing


nStein et al.


Lots of partnerships


Linguistics all the way down

In this market, semantics
is

central



Sophisticated taxonomies


Sentiment extraction!


Syntax is often important too

Six trends that could shake up the market



Web/enterprise/messaging integration


BI integration


Universal message retention


Portable personal profiles


Electronic health records


Voice command & control …


… and semantics plays (or should play) a big role in
all of them.




Further information


Curt A. Monash, Ph.D.

President, Monash Research

Editor,
Text Technologies


contact@monash.com

http://www.monash.com

http://www.texttechnologies.com