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DAML Agent Semantic Communications Service (ASCS) Teknowledge Adam Pease, John Li [apease | July 19, 2001.

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Presentation on theme: "DAML Agent Semantic Communications Service (ASCS) Teknowledge Adam Pease, John Li [apease | July 19, 2001."— Presentation transcript:

1 DAML Agent Semantic Communications Service (ASCS) Teknowledge Adam Pease, John Li [apease | July 19, 2001

2 Whats Hot Scaleable DAML-based search engine –Experiments to quantify performance –Includes translation between ontologies Large ontologies in DAML Commercial product integration –TekPortal

3 Whats Hard Scaling semantic search Ontology translation –Finding a useful set of transformations (not arbitrarily complex stuff that isnt used) Creating a compelling value proposition for commercial product (the UHF problem)

4 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 Analyst Agent Ontology Agent Ontology Agent Ontology Shared ontology Database Web Pages Shared ontology Shared ontology Shared ontology ASCS Agent ASCS Agent ASCS Agent ASCS Agent

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

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 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 1,007 records ,019 10,044 records , ,033 records , ,7262,000 1,6803,5643,4675,14810,74310,080 Simple Queries (in ms) Complex Queries (in ms) Size of DB S1 S2 S3 S1 S2 S3 1,000,004 records 1,007 records ,019 10,044 records , ,033 records , ,7262,000 1,6803,5643,4675,14810,74310,080 Simple Queries (in ms) Complex Queries (in ms) Size of DB S1 S2 S3 S1 S2 S3 1,000,004 records 1,007 records ,019 10,044 records , ,033 records , ,7262,000 1,6803,5643,4675,14810,74310,080 Simple Queries (in ms) Complex Queries (in ms) Size of DB S1 S2 S3 S1 S2 S3

8 Large Ontologies WordNet in DAML –10,000 pages each with 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 Query Interface Result pages for queries, bond listing, Financial App. TekPortal Calls SQL Queries Data Results as Strings TekPortal JSP SQL Server Result page for TekPortal info. SSA2 STA SSA3 Bond 1 Server Bond 2 Server Financial App. Result page for Fin. App SSA1 Architecture

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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