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The trick is to see the
intrinsic patterns in language
biologically inspired intelligence


© ai-one inc. 2012
                                     ai-one™
Biologically Inspired Intelligence




                     logic   creativity




© ai-one inc. 2012
Make sense of any* text
Recognize the sense and meaning within a
text corpus means to identify the most
semantically important words in the text




* as long as there is sense in the unstructured sentences…


© ai-one inc. 2012
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                                                                   ai-one
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 © ai-one inc. 2012
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 © ai-one inc. 2012
ANY Language!




 © ai-one inc. 2012
ANY Language!




 © ai-one inc. 2012
prolitterisdorerchristianvaldaandreasblick20020129seite5nummer23swissairboss12miofür5jahreimvora
ANY Language!
uskassiertderdruckwächstcortiindeckungvonchristiandorerundandreasvaldazürichesistvölligunüblichd
assderlohnfürfünfjahreimvorausbezahltwirdsagenrenommierteheadhunterfdppräsidentgeroldbührer53v
erlangtjetztschonungslostransparenznochimmersagenmariocortiundseinefreundeausdemaltenverwaltu
ngsratnocommentcortiweiltegesterninpolenundwolltenochimmernichtsagenoberaufeinenteilseines5jahr
eslohnesverzichtenwirdinschweigenhüllensichauchdieehemaligenverwaltungsrätedieimmärz2001denve
rgoldetencortivertragaufgesetzthattenindersalärkommissionsassdamalszementkönigthomasschmidhein
y56herrschmidheinymöchtesichnichtäussernsolangedieuntersuchungdessachwaltersläuftlässterausric
htengleichtöntesbeimzweitenkommissionsmitgliedgaudenzstaehelinichhabeverständnisfürdasinteresse
aberesliegtanderswissairzuinformierennichtanmirauchdieübrigenmitgliedervonvrenispoerrybislukasmü
hlemannverkriechensichdabeiwarenauchsiebestensimbildsolcheverträgewurdenimmerimplenumbespro
chensagteinehemaligesvrmitglieddochcreditsuissechefmühlemann51bequemtsichgenausowenigzueine
roffeneninformationwiebankierbénédicthentsch53amtelefonsagterentnervtichhabedasrechtnichtszusag
enwarumwollensienichtssagenherrhentschfragensienichtweiterichgebekeinenkommentarschönentagau
fwiedersehenaufgehängtjetztregtsichpolitischerwiderstandwennderbetragohneauflagenüberzieleausbez
ahltwurdedannistdasinakzeptabelsagtfdppräsidentgeroldbührerüberfdpmitgliedcortijetztbrauchtesschn
elltransparenzdenkopfschütteltauchcvppräsidentphilippstähelin57ichhabemühemiteinemsohohenlohnd
asführtzuriesigeneinkommensunterschiedenimvolkdasdarfnichtseinerhaltezwarvielvonleistungslohndo
chdenkannmannichtimvorausbekommenvorauszahlungensindunüblichsagtheadhuntersandrovgianellau
ndfredyislervonspencerstuartichhabenochnievoneinemsolchenfallgehörtaberniemandwolltedenswissair
jobdiesesversprechenwarwohleinlockvogeldamitcortiseinensicherennestlépostenaufgabmariocortiluka
smühlemannthomasschmidheinybénédicthentschkonzernsanierermussvorgerichtzürichdervorkassever
tragcortisistkeinepremiereimfallderkonkursitenbiberholdingliesssichkonzernsaniererchristianspeiserbil
dseinenjobmit28millionenfrankengarantielohnvergoldenermusssichjetztvorgerichtverantwortenwiecorti




   © ai-one inc. 2012
ANY Language!
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  © ai-one inc. 2012
ANY Language!
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  © ai-one inc. 2012
Light Weight Ontology (LWO)!
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  © ai-one inc. 2012
Lightweight Ontology (LWO)
Association Strength
  physical exercise                     smoking

                 0.9                     0.9
                            lifestyle
                     0.75   0.6         0.9

           stress           obesity     nutrition

 Our technology detects the strength of all associations between all words
 (n:n). The LWO captures the intrinsic semantic value of every word,
 sentence, etc. ai-one is self-learning, self-organizing and incrementally
 self-updating




© ai-one inc. 2012
              2010
Be careful: The semantic trap!
Every human interprets semantics differently because of
experience, intellectual level, cognitive biases, etc.

                       Sender                      Receiver




  subjective meaning                                          Subjective interpretation
  and semantic                                                & understanding


                     ai-one has the neutral observer position
                          to detect the inherent meaning




                             ai-one shows the LWO
                           regardless if right or wrong


© ai-one inc. 2012
From LWO to one ai-fingerprint
Convert the LWO-pattern in a simple visualization with
graph charts to show, store & match fingerprints




© ai-one inc. 2012
Use case: ai-fingerprint to match
job posting with resumes for HR
                     job                job                • jobs -> c.v.
                                                           • c.v. -> jobs
                                                    c.v.
       job                                                      • similar text
                           job                                  • similar meaning
                                              job

                                                            • data in forms -> free text
             c.v.
                                                            • free text -> forms
                                 c.v.

                                         • Dynamic
                                         • Intelligent

© ai-one inc. 2012
ai-fingerprint as bridge to traditional
approaches
                     The fingerprint is defined by the the most important words of a text
                     corpus – called keywords. Keywords words are classified in
                     importance according to a value determined by ai-one.

                     Keywords can be used to search with Yahoo, Google, Wolfram
                     Alpha, Bing and any other search approach.

                     Since the keywords are the optimal search words, users will get the
                     best answer by traditional search engine.

                     Spicing          with the ai-fingerprint
                     semantic for better results.




© ai-one inc. 2012
ai-fingerprint solves an other problem
in traditional text analytics
We solve the problem of identifying multiple themes in a single
document. Very often, there are multiple items, issues or themes on the
same page.

For example in a news magazine, there are short article about different
subjects on the same page. This is very challenging for traditional
semantic text analysis processes.

ai-one’s LWO automatically segments topics into related clusters.




© ai-one inc. 2012
ai-Fingerprint
Typical ai-fingerprint of a text corpus very focused on
one issue/theme.




© ai-one inc. 2012
              2010
ai-Fingerprint
Typical ai-fingerprint of a text corpus where tree
different issues/themes are on the same page

                              1
                     1


                                  2
                     2

                                            3
                     3


© ai-one inc. 2012
              2010
ai-Fingerprint
Typical ai-fingerprint of a “nonsense”-text corpus where
no real sentences are giving an story, randomly sentences




© ai-one inc. 2012
              2010
ai-Fingerprint
Enables better decision making by providing a way to
compare semantic content by using graphs.




© ai-one inc. 2012
              2010
…ai-one –
… much better than any
  traditionally method….!

Current linguistics and semantic solutions
works only if they are feed with accurate and
detailed language dependent models.

Worse, they do NOT incrementally update or
learn!

© ai-one inc. 2012
              2010
…ai-one – the next
 evolution stage in ICT?

… recognizing the content
… understanding the meaning and
  generalizing its application
… deciding about its importance
… knowing what to do with this
  learned information

© ai-one inc. 2012
              2010
Thank You!

ai-one inc.            ai-one ag            ai-one gmbh
5711 La Jolla Blvd.,   Flughofstrasse 55,   Koenigsallee 35a,
Bird Rock              Zürich-Kloten        Grunewald
La Jolla, CA 92037     8152 Glattbrugg      14193 Berlin

info@ai-one.com
www.ai-one.com



© ai-one inc. 2012

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03 ai-one - overview - ai-fingerprint