Communicative evolution: from strings to words to expressions to concepts to intentions Piek Vossen ©Irion Technologies ICT Kenniscongres, April 11 th,

Communicative evolution:from strings to words to expressions to concepts to intentionsPiek Vossen

©Irion Technologies

ICT Kenniscongres, April 11th, 2006


Irion Technologies: The company

Founded in 2000 as a spin-off from TNO Multimedia Technology

5 investors: Parcom Ventures, FLV, Twinning, TNO, Van Dale The people

About 10 language technology and computer science specialists. Collaboration with teams at Van Dale and TNO.

The mission Equal access to the knowledge and information on the Internet

to all people, regardless of language and background Develop systems that understand language


Product TwentyOne

XML

Publishing Platform

Concept extraction

Translation

Indexing

Classification

Summarization

Crawl

Copy

Convert

Split

Web documents

Paper documents

Word Processor

Documents

Databases

AV Documents

ConceptualConceptualIndexingIndexing ( (NLPNLP))

Search

Capture

Cockpit

DialogueMatch /Mining


Strings Strings

Expression in language

Words….


….Words

Strings

Concept

Query

Concept

InformationSeeker

InformationProvider

Information

ape

….

energy

….

mass

….

….

zebra

Index of Strings


Strings Strings


my cell phone….


….mobile

Strings

Concept Concept

Query Information

InformationSeeker

InformationProvider

ape

….

….

….

mobile

….

….

zebra

Index of Strings

Conceptual match

Linguistic mismatch


Strings Strings


my cell phone….


….nerve cells

Strings

Concept Concept

Query Information

InformationSeeker

InformationProvider

ape

….

cell

….

….

….

….

zebra

Index of Strings

Conceptual mismatch

Linguistic match


Strings Strings


police cell ….


…. nerve cells

Strings

Concept Concept

Query Information

InformationSeeker

InformationProvider

ape

….

cell

….

….

….

….

zebra

Index of Strings

Conceptual mismatch

Linguistic match


Strings Strings


neuron ….


….nerve cells

Strings

Concept Concept

Query Information

InformationSeeker

InformationProvider

ape

….

cell

….

….

….

….

zebra

Index of Strings

Conceptual match

Linguistic mismatch


Recall & Precision

query:

“cell”

Search engine for

fatabase with

all documents

“cell

phone”

“mobile

phones”

“nerve cell”

“police cell”

recall = doorsnede / relevant

precision = doorsnede / gevonden

found intersection relevant

Recall < 20% for basic search engines!

(Blair & Maron 1985)


Synonyms,Semantic network

thesaurus

golfclub(s)

Tiger

Woods

golf

sticks

Language technology: a hole in one!

golfclubs

Linguistic analysis

at the club

clubs

for golf


Information systems lack a communicative model Language is an instrument for communication:

Not fully descriptive Minimal & sufficient information for a

communicative effect Speakers/writers make assumptions about the

addressee: Knowledge of the world Knowledge of language Knowledge about the communicative settings


Communicative models in a robust and scalable system Index of concepts instead of strings

Meaning of a word in context: Domain of the document:

Juventus => football Topic of the paragraph:

transfer scandal => business, crime Phrase: linguistically-motivated combination of words:

[wing player]football player in [police cell]jail

Topic of the query: Can I order chicken wings? => food

Phrase: [chicken wings]dish

Multilingual semantic networks in many languages to map words to concepts

Concept matching calculus for comparing query phrases with phrases in documents


Dialogue system that cooperates with user: Detect intention: complaint, buy, support, information Measure satisfaction: happy, emotions Avoid deadlocks:

Detect vagueness or ambiguity (what meaning of cell?) Detect topic shifts Handle negative information: “No phones, I want jails!” Allow to change perspective Ask user for help, directions, confirmation and explication

Create more context than simple key words and deliver more precision: answers instead of hits.

Communicative models in a robust and scalable system


Dialogue system

ClassifierEngine

DialogueManager

RetrievalEngine

• Can I help you?• My head phone does not work?

• I want to buy a new one.

• Are you looking for support or products?

• Can you tell me more about the product?• It is for my cell phone• Can you give me more details?

• It is a Nokia 338• I found the following accessories for you. Please have a look.

Concepts

Facts

Model Price In stockUserModel-Intention-Satisfaction-Emotion

InformationState:-Positives-Negatives-Relations

• Thats not what I want

cellphone

accessories

repair

support

PhrasesUtteranceTyper


Research & Development

Starting point in 2000: Retrieval technology from TNO (10 years research) Language resources from Van Dale (decades of work)

Research projects: MEANING (IST-2001-34460), 2002-2005 PIDGIN (CIC-programme), 2002-2004 Global Wordnet Association, 2000 – ongoing Aarhus (Provincie Gelderland ICT), 2005 - 2006 Kenniswijk (Senter Novem), 2005-2006 Gemeente Connect (STEVIN), 2005-2006 Cornetto (STEVIN), 2006 - 2008


MEANING (IST-2001-34460)

Funded by the EU, 2002-2005 Conceptual index and conceptual matching Extended search engine (EN, NL, DE, FR, IT,

ES) to cover also Basque and Catalan Doubled (!) production in end-user scenario

of Spanish publisher EFE. Extended in Aarhus project


PIDGIN

Funded in the CIC-programme, 2002-2004 Cross-lingual chat application English-Dutch Sign-post dialogue system that searches

information: In a collaborative task between user and machine Without the need to build a model of the world Can be applied to unlimited amounts of

unstructured data Extension: Kenniswijk, GemeenteConnect


Global Wordnet Association:http://www.globalwordnet.org Stimulates the development and interlinking

of semantic networks for all languages in the world

World-wide Semantic Grid: mapping of all languages to a single set of concepts

Currently 39 languages and extending Bi-annual conference: India (2002), Czech

(2004), Korea (2006) Extended for Dutch in Cornetto