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DAML Agent Semantic Communications Service (ASCS)

DAML Agent Semantic Communications Service (ASCS). Teknowledge Adam Pease, John Li [apease | jli]@teknowledge.com July 19, 2001. What’s Hot. Scaleable DAML-based search engine Experiments to quantify performance Includes translation between ontologies Large ontologies in DAML

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DAML Agent Semantic Communications Service (ASCS)

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  1. DAMLAgent Semantic Communications Service (ASCS) Teknowledge Adam Pease, John Li [apease | jli]@teknowledge.com July 19, 2001

  2. What’s Hot • Scaleable DAML-based search engine • Experiments to quantify performance • Includes translation between ontologies • Large ontologies in DAML • Commercial product integration • TekPortal

  3. What’s Hard • Scaling semantic search • Ontology translation • Finding a useful set of transformations (not arbitrarily complex stuff that isn’t used) • Creating a compelling value proposition for commercial product (the UHF problem)

  4. Ontology Ontology Agent Agent Analyst Ontology Web Agent Pages Semantic Search • Agent Semantic Communications Service (ASCS) • Integration between agents with different ontologies • Semantic Search Engine (SSE) • An agent doing smart searches for other agents • Semantic translation service • Translates between ontologies ASCS ASCS Agent Agent Database Shared Shared ontology ontology Shared ontology Shared ASCS ontology Agent ASCS Agent

  5. Search translatorList recentSearchID Search Agent Search Agent Search Agent Translator transForSearch() transForResult() Index Index Index Architecture GUI Query orginalQuery originalOntology currentQuery currentOntology hoplist timeoutLimit hopcountLimit searchID searchResultFlag rdfResultList Query Query Translator Query Query Translator Query

  6. Areas of Application • ASCS applies to passive information (e.g. web pages) and active agents (e.g. planners, databases, shoppers, search engines) • ASCS also helps with ontology versioning problems

  7. Simple Queries (in ms) Simple Queries (in ms) Simple Queries (in ms) Complex Queries (in ms) Complex Queries (in ms) Complex Queries (in ms) Size of DB Size of DB Size of DB S1 S1 S1 S2 S2 S2 S3 S3 S3 S1 S1 S1 S2 S2 S2 S3 S3 S3 1,007 records 1,007 records 1,007 records 176 176 176 565 565 565 691 691 691 205 205 205 706 706 706 1,019 1,019 1,019 10,044 records 10,044 records 10,044 records 189 189 189 595 595 595 655 655 655 296 296 296 802 802 802 1,138 1,138 1,138 100,033 records 100,033 records 100,033 records 592 592 592 924 924 924 1,069 1,069 1,069 709 709 709 1,726 1,726 1,726 2,000 2,000 2,000 1,680 1,680 1,680 3,564 3,564 3,564 3,467 3,467 3,467 5,148 5,148 5,148 10,743 10,743 10,743 10,080 10,080 10,080 Experimentation • Quantitative Experiments not “Existence proofs” • Metrics include: inter-agent communication speed (as mediated by ASCS), correctness of the translation, semantic complexity of source and target communication 1,000,004 records 1,000,004 records 1,000,004 records

  8. Large Ontologies • WordNet in DAML • 10,000 pages each with 10-100 DAML statements • IEEE Standard Upper Ontology (proposal) • Large, free, general purpose, formal, peer-reviewed • People are free to reuse all or part of the content • A resource to speed creation of good ontologies and avoid reinvention • ~2000 DAML statements

  9. Commercial Product • TekPortal • Industry leader in on-premise account aggregation • In use at NetBank, MacQuerie, 30+ financial institutions • VARs include NCR, Vexis, and Financial Fusion Inc

  10. TekPortal + DAML • Financial ontology in DAML (and built on the SUO proposal) • DAML encoded aggregation displays • DAML markup of bond sites • Ontology translation • Crawl and index bond sites • Dynamic search, translation, advice

  11. Architecture SSA2 Bond 1 Server Result pages for queries, bond listing, Financial App. SSA3 STA Bond 2 Server Query Interface SSA1 Financial App. Result page for Fin. App Results as Strings TekPortal JSP TekPortal Calls SQL Queries Data SQL Server Result page for TekPortal info.

  12. Bond Information

  13. Account Aggregation

  14. Advice

  15. Plans • Semi-automated discovery of translations • DAML-based advice and inference • Additional DAML ontologies • Deployment of client and server-based search agents • Multi-user DAML-based advice server • Improved general search interface

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