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

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Presentation on theme: "Communicative evolution: from strings to words to expressions to concepts to intentions Piek Vossen ©Irion Technologies ICT Kenniscongres, April 11 th,"— Presentation transcript:

1 Communicative evolution: from strings to words to expressions to concepts to intentions Piek Vossen ©Irion Technologies ICT Kenniscongres, April 11 th, 2006

2 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

3 ICT Kenniscongres, April 11th, 2006 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 Conceptual Indexing (NLP) Search Capture Cockpit Dialogue Match / Mining

4 ICT Kenniscongres, April 11th, 2006 Strings Expression in language Words…. Expression in language ….Words Strings Concept Query Concept Information Seeker Information Provider Information ape …. energy …. mass …. zebra Index of Strings

5 ICT Kenniscongres, April 11th, 2006 Strings Expression in language my cell phone…. Expression in language ….mobile Strings Concept QueryInformation Seeker Information Provider ape …. mobile …. zebra Index of Strings Conceptual match Linguistic mismatch

6 ICT Kenniscongres, April 11th, 2006 Strings Expression in language my cell phone…. Expression in language ….nerve cells Strings Concept QueryInformation Seeker Information Provider ape …. cell …. zebra Index of Strings Conceptual mismatch Linguistic match

7 ICT Kenniscongres, April 11th, 2006 Strings Expression in language police cell …. Expression in language …. nerve cells Strings Concept QueryInformation Seeker Information Provider ape …. cell …. zebra Index of Strings Conceptual mismatch Linguistic match

8 ICT Kenniscongres, April 11th, 2006 Strings Expression in language neuron …. Expression in language ….nerve cells Strings Concept QueryInformation Seeker Information Provider ape …. cell …. zebra Index of Strings Conceptual match Linguistic mismatch

9 ICT Kenniscongres, April 11th, 2006 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 foundintersectionrelevant Recall < 20% for basic search engines! (Blair & Maron 1985)

10 ICT Kenniscongres, April 11th, 2006 Synonyms, Semantic network thesaurus golf club(s) Tiger Woods golf sticks Language technology: a hole in one! golf clubs Linguistic analysis at the club clubs for golf

11 ICT Kenniscongres, April 11th, 2006 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

12 ICT Kenniscongres, April 11th, 2006 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

13 ICT Kenniscongres, April 11th, 2006 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

14 ICT Kenniscongres, April 11th, 2006 Dialogue system Classifier Engine Dialogue Manager Retrieval Engine 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 ModelPriceIn stock User Model -Intention -Satisfaction -Emotion Information State: -Positives -Negatives -Relations Thats not what I want cell phone accessories repair support Phrases Utterance Typer

15 ICT Kenniscongres, April 11th, 2006 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 ), PIDGIN (CIC-programme), Global Wordnet Association, 2000 – ongoing Aarhus (Provincie Gelderland ICT), Kenniswijk (Senter Novem), Gemeente Connect (STEVIN), Cornetto (STEVIN),

16 ICT Kenniscongres, April 11th, 2006 MEANING (IST ) Funded by the EU, 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

17 ICT Kenniscongres, April 11th, 2006 PIDGIN Funded in the CIC-programme, 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

18 ICT Kenniscongres, April 11th, 2006 Global Wordnet Association: 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


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