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KR: Reinjecting Reality

But, once they are so conceived, the subject begins to live a peculiar life of its own ... Examples from http://dormouse.cs.umd.edu:8080/wiki/cmsc498wiki.wiki. Students violated ...

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KR: Reinjecting Reality

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    1. KR: Reinjecting Reality

    Mathematical ideas originate in empirics .. But, once they are so conceived, the subject begins to live a peculiar life of its own and is better compared to a creative one, governed almost entirely by aesthetical motivations …As a mathematical discipline travels, or after much abstract inbreeding, [it] is in danger of degeneration…whenever this stage is reached, the only remedy seems to me to be the rejuvenating return to the source; the reinjection of more or less directly empirical ideas --- John Von Neumann, 1953

    2. The Semantic Web: KR’s Worst Nightmare?

    Professor James Hendler http://www.cs.umd.edu/~hendler Co-Director, Maryland Information and Network Dynamics Laboratory

    3. The nightmare: KR becomes relevant

    Artificial Intelligence researchers have studied such systems since long before the web was developed. Knowledge representation, as this technology is often called, is currently in a state comparable to that of hypertext before the advent of the web: it is clearly a good idea, and some very nice demonstrations exist, but it has not yet changed the world. It contains the seeds of important applications, but to unleash its full power it must be linked into a single global system. -- Tim Berners-Lee, inventor of the WWW, 2001.

    4. Outline

    The SEMANTIC web The semantic WEB We’ve heard this kind of crap before, why should we believe this one? Challenges ahead But is it AI?

    5. The SEMANTIC Web

    6. KR on the Web

    Many characteristics of the Web violate traditional KR assumptions! It's Large and It Grows Fast High Variety in Quality of Knowledge Diversity of Content Unknown/unpredictable Use Scenarios for the Knowledge Problems of Trust, No Single Authority Lack of Referential Integrity Knowledge acquired, not engineered (Van Harmelen, 2000)

    7. Web Semantics

    Semantic Web LayerCake (Berners-Lee, 99;Swartz-Hendler, 2001)

    8. Putting semantics on the web

    9. (and making it machine-readable)

    10. Can’t we just use XML?

    This is what a web-page in natural language looks like for a machine

    11. XML helps

    XML allows “meaningful tags” to be added to parts of the text

    12. XML ? machine accessible meaning

    But to your machine, the tags look like this….

    13. Schemas take a step in the right direction

    Schemas help…. < CV > …by relating common terms between documents private

    14. But other people use other schemas

    < CV > ?name> <educ> <> <????> Someone else has one like this….

    15. The “semantics” isn’t there

    < CV > …which don’t fit in private

    16. KR provides “external” referents to merge on

    SW languages add mappings And structure. nme work vate educ CV CV CV educ

    17. Which is what the web was meant to be!!

    "This is a pity, as in fact documents on the web describe real objects and imaginary concepts, and give particular relationships between them... For example, a document might describe a person. The title document to a house describes a house and also the ownership relation with a person. ... This means that machines, as well as people operating on the web of information, can do real things. For example, a program could search for a house and negotiate transfer of ownership of the house to a new owner. The land registry guarantees that the title actually represents reality.” Tim Berners-Lee plenary presentation at WWW Geneva, 1994

    18. The semantic WEB

    (Genome World - from Goble, 01) Goal: do to ontologies what the web does for documents

    19. This leads to a radically new view of interoperation

    Distributed,partially mapped, inconsistent -- but very flexible! = some partial mapping

    20. But, like the web…

    21. Real examples

    Examples from http://dormouse.cs.umd.edu:8080/wiki/cmsc498wiki.wiki Students violated every rule in the KR book Extended existing ontologies Linked instances directly to terms from multiple ontologies Mixed “real KR” and NL We can learn from their lessons http://dormouse.cs.umd.edu:8080/wiki/assignment1_collected_les.wiki

    22. But will it fly

    DAML+OIL is probably the most used AI language ever!! http://www.daml.org Gaining acceptance by web players Semantic Web Track being offered at WWW 2002 More people will attend WWW2002 Developer Day on SW than attend KR Significant (international) Govt Support US DARPA/NSF; EU IST Framework 5,6 Japan, Germany, Australia considering significant investments US National Cancer Institute to publish cancer vocabulary in DAML+OIL Much New Startup activity (even in this economic climate) Many tools being developed Many of them aimed at developers, not just AI literate types

    23. W3C Web Ont WG

    Current Working Group includes over 50 members from 30+ organizations. Industry including: Large companies such as Sun, IBM, HP, Intel, EDS, Fujitsu, Lucent, Nokia, Philips Electronics, Unisys, Daimler0Chrysler Newer/smaller companies such as IVIS Group, Network Inference, Stilo Technology, Unicorn Solutions Government and Not-For-Profits: US Defense Information Systems Agency, Interoperability Technology Association for Information Processing, Japan (INTAP) , Electricite De France, Mitre Universities and Research Centers: University of Bristol, University of Maryland, University of Southamptom, Stanford University DFKI (German Research Center for Artificial Intelligence), Forschungszentrum Informatik, Ontoweb Invited Experts (From non-W3C members) Well-known KR researchers (Hayes, Stein) Tool Developers (Dean, Heflin) Domain experts (Borden) W3C Team Connolly (HTML, XML. XML-schema); Brickley (RDF, RDF Core)

    24. Moving to the futureof the web

    Semantic Web LayerCake (Berners-Lee, 99;Swartz-Hendler, 2001)

    25. Web “travel agents”

    Query processed: 73 answers found Google document search finds 235,312 possible page hits. Http://www…/CowTexas.html claims the answer is 289,921,836 A database entitled “Texas Cattle Association” can be queried for the answer, but you will need “authorization as a state employee.” A computer program that can compute that number is offered by the State of Texas Cattleman’s Cooperative, click here to run program. ... The “sex network” can answer anything that troubles you, click here for relief... The “UFO network” claims the “all cows in Texas have been replaced by aliens How many cows are there in Texas?

    26. Web Agents need Service Descriptions

    27. Services need Web Logics

    28. Web of Trust

    Claims can be verified if there is supporting evidence from another (trusted) source We only believe that someone is a professor at a university if the university also claims that person is a professor, and the university is on a list I trust. believe(c1) :- claims(x, c1) ^ predicate(c1, professorAt) ^ arg1(c1, x) ^ arg2(c1, y) ^ claims(c2, y) ^ predicate(c2, professorAt) ^ arg1(c2, x) ^ arg2(c2, y) ^ AccreditedUniversity(y) AcknowledgedUniversity(u) :- link-from(“http://www.cs.umd.edu/university-list”,u) Notice this one

    29. Validation sites

    Buy into your favorite rule set believable(x) :- claims(src,x) ^ accreditedbyChristianCoalition(src) believable(x) :- claims(src,x) ^ linkfromMomsPage(src) believable(x) :- claims(src,x) ^ accreditedby(“http://foo.com/Unabomber/Friends/rules”,src) ^ Not-accreditedbyChristianColation(x)

    30. But is it AI ?

    What about human intelligence It's Large and It Grows Fast Lack of Referential Integrity High Variety in Quality of Knowledge Diversity of Content Unknown/unpredictable Use Scenarios for the Knowledge Problems of Trust, No Single Authority Knowledge acquired, not engineered Many characteristics of human intelligence violate traditional KR assumptions It’s time for us to face up to the real challenge!!

    31. Conclusion

    It is no longer a question of whether the semantic web could come into being, it can and will We’re already well past the starting gate Web ontologies, term languages, “shims” to DB and services, research in proofs/rules/trust Standardization providing a common denominator for KR researchers as well as web developers Small companies starting to form, Big companies starting to move The KR community has lots to offer If, and maybe only if, it is willing to revisit some basic assumptions The current environment is open, encouraging, moving fast, and exciting as heck Come play!

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