Re: http://ontolog.cim3.net/cgi-bin/wiki.pl?ConferenceCall_2013_06_20 (01)
Dear All, (02)
I am happy to announce two very exciting "Ontolog Invited Speaker"
sessions that will be featured in the upcoming Thursdays. We are
honored to have two individuals, who have been working at the cutting
edge of the technologies near-and-dear to us, to share with us their
work and insights. (03)
You are cordially invited to join us at these sessions. ... RSVP now!
... details below. (04)
******************* Hightlights ******************* (05)
* Thu 20 Jun 2013 - Ontolog Invited Speaker, Dr. Benjamin Grosof,
giving a talk on "Rulelog: Highly Expressive yet Scalable Logic
enabling Cost-Efficient Ontologies" - Chair: Dr. Leo Obrst - see
details on the session page at:
http://ontolog.cim3.net/cgi-bin/wiki.pl?ConferenceCall_2013_06_20 ...
RSVP now! (06)
* Thu 27 Jun 2013 - Ontolog Invited Speaker, Dr. Vinay Chaudhri,
giving a talk on "KB_Bio_101: Conceptual Modeling Challenges in
Creating a Biology Knowledge Base" - Chair: Dr. Leo Obrst - see
details on the session page at:
http://ontolog.cim3.net/cgi-bin/wiki.pl?ConferenceCall_2013_06_27 (07)
*Register your attendance* by emailing <peter.yim@xxxxxxxx> off-line
or register yourself directly to the wiki session page. Please specify
the date or name of the session(s) you are registering for (your
affiliation too, if you are not already a member of the community.)
... RSVP (08)
***************************************************** (09)
Now, for next Thursday's session ... (010)
= Ontolog Invited Speaker Presentation - Dr. Benjamin Grosof - Thu 2013.06.20 = (011)
Session Chair: Dr. Leo Obrst (Ontolog; MITRE) (012)
Invited Speaker: Dr. Benjamin Grosof (Benjamin Grosof & Associates;
Coherent Knowledge Systems) (013)
Title of Presentation: "Rulelog: Highly Expressive yet Scalable Logic
enabling Cost-Efficient Ontologies" (014)
== Abstract == (015)
We present Rulelog, a new logic that is highly expressive yet
scalable, and Textual Logic, a related new approach to natural
language processing that does logic-based mapping between English text
and Rulelog knowledge. We have developed their theory and
implementation techniques in over a decade of research work, including
in Vulcan's SILK and Project Halo, jointly with many others. A
commercial implementation is underway from Coherent Knowledge Systems,
a new startup. RIF-Rulelog is in draft as an industry standard
submission to W3C from RuleML. (016)
Rulelog extends normal declarative logic programs (LP) to permit
defeasible higher-order logic formulas but achieves computational
tractability. Two keys to that tractability are: avoiding unrestricted
reasoning-by-cases; and restraint, a kind of bounded rationality that
leverages the third truth value ("undefined") in the well founded
semantics. Flora-2, an open-source semantic rule engine (built on top
of open-source XSB Prolog), implements most of Rulelog's
expressiveness. (017)
Rulelog is a "big tent" knowledge representation (KR) that is sound
semantically relative to classical logic (e.g., OWL-DL and Common
Logic), in addition to supersuming LP (e.g., SPARQL, SQL, and
essentially RIF-BLD, OWL-RL/RDF(S), and semantic production rules).
Knowledge can thus be translated semantically into Rulelog from all of
the above, typically without major (or, in many cases, any) practical
information loss. (018)
Rulelog's expressive power enables cost-efficient knowledge
acquisition (KA), including about ontologies. KA can start from
effectively unrestricted English, via Textual Logic, which includes: (019)
1. Rapid interactive logical disambiguation: Effectively
unrestricted English sentences can be semi-automatically disambiguated
into Rulelog in rapid fashion. In a pilot study in the domain of
college-level biology, roughly 10 minutes of labor per sentence was
required by knowledge engineers, using Automata Linguist, a new tool. (020)
2. Textual terminology: Any English phrase corresponds one-to-one to
a logical term. Ontological terminology emerges naturally and
automatically from English text's phraseology, instead of requiring
laborious separate specification and social agreement. This leverages
background lexical ontological knowledge about English, available
open-source. (021)
In addition, Rulelog's expressive power enables: (022)
3. Seamless mapping: Ontology mappings can be represented concisely
and flexibly, and tightly combined in the same
logic/system/knowledge-base with ontologies and rules/facts knowledge
that employs the ontologies' terminology. (023)
4. Inheritance with exceptions: Ontologies based on class
hierarchies can be made more concise and reusable by allowing
inheritance to have exceptions, rather than requiring inheritance to
be strict (as in OWL/RDF(S)). (024)
== About the Speakers == (025)
Benjamin Grosof is an industry leader in knowledge representation,
reasoning, and acquisition. He has pioneered semantic technology and
industry standards for rules, the combination of rules with
ontologies, the applications of rules in e-commerce and policies, and
the acquisition of rules and ontologies from natural language (NL). He
has had driving roles in RuleML, W3C RIF (Rule Interchange Format),
and W3C OWL-RL (rule-based ontologies). He led the invention of
several fundamental technical advances in knowledge representation,
including courteous defeasibility, restraint bounded rationality, and
the rule-based technique which rapidly became the currently dominant
approach to commercial implementation of OWL. He has extensive
experience in machine learning, probabilistic reasoning, and user
interaction design. (026)
Dr. Grosof has experience applying core technology for knowledge,
reasoning, and related HCI in a wide variety of application areas,
including: trust/privacy/security, contracts, compliance, legal, and
services engineering; financial/insurance services, risk management,
and regulations; defense and national intelligence; biomedical
research; and data/decision analytics. From fall 2007 to early 2013,
he led a large research program in Artificial Intelligence (AI) and
rule-based semantic technologies at Vulcan Inc. for Paul G. Allen;
this centered around the SILK system for highly expressive, yet
scalable, rules. Previously he was an IT professor at MIT Sloan
(2000-2007) and a senior software scientist at IBM Research
(1988-2000). He is president of the expert consulting firm Benjamin
Grosof & Associates founded while he was at MIT, and is affiliate
faculty in the AI group at U. Washington. His background includes 4
major industry software releases, 2 years in software startups, a
Stanford PhD (Computer Science), a Harvard BA (Applied Mathematics), 2
patents, and over 50 refereed publications. (027)
****************** (028)
These sessions, like all Ontolog virtual events, are open and free of
charge. Anyone who is interested, or (better still) who may have
something to contribute, is welcome. Please refer to event details on
the session pages, to which the hyperlink is given above, where you
will find session agenda, conference call dial-in, slides and other
pertinent information. Feel free to pass this invitation along to
colleagues who may also find these sessions to be of interest. (029)
*RSVP* by emailing Peter Yim at <peter.yim@xxxxxxxx> offline (or add
yourself directly to the session page if you are already an Ontolog
community member) so that we can prepare enough resources to support
everyone. [Please state clearly the date of the session you are
registering for in your email; your affiliation too, if you are not a
community member.] (030)
These sessions will be recorded and made available in a publicly
accessible archive. Therefore, before participating, please make sure
you are cognizant of our IPR policy (ref:
http://ontolog.cim3.net/cgi-bin/wiki.pl?WikiHomePage#nid32). (031)
Regards. =ppy (032)
For the Session Chair
Leo Obrst
-- (033)
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