DAML Tools for Intelligent Information Annotation, Sharing and Retrieval

1
DAML Tools forIntelligent Information
Annotation, Sharing and Retrieval

• UMBC
• Johns Hopkins University Applied Physics Lab
• MIT Sloan School
• July 19, 2001

2
UMBC/JHU/MIT Team

• UMBC, JHU/APL, and MIT/Sloan are working together
  on a set of issues
• UMBC
• Integrating communicating agents, DAML and web
  applications
• Tim Finin, Charles Nicholas, Yun Peng, Anupam
  Joshi, Scott Cost
• JHU APL
• DAML and information retrieval
• Jim Mayfield, Paul McNamee, Wayne Bethea
• MIT Sloan School
• DAML, rules based technology and distributed
  belief
• Benjamin Grosof
• To be integrated in agent-based applications
  involving search and using rule-based reasoning.

DEMO
DEMO
3
UMBC

• WHAT'S HOT?
• ITTALKS as a useful DAML-based application
• Automatic classification of talks and users wrt
  DAML topic ontologies multiple topic ontologies,
  with manual and mapping between them.
• Agents get DAML talk notifications and make
  entries on a users calendar if it matches
  interests, location and schedule.
• Agents use DAML as ACL and incorporate a DAML
  reasoning engine (XSB, YAJXB, RDF API)
• A DAML distributed trust model including
  permissions, obligations, authorization and
  delegation.
• DAMLized Jini registration service
• DAMLized Bluetooth service discovery protocol

• CHALLENGES!
• Need for a range of DAML reasoning engines
• Offering varying degrees of services and
  completeness
• Implementations in Java?
• Full DAML may be too large for some interesting
  applications
• e.g., using in Jini for light-weight devices
• e.g., use in Bluetooth service discovery protocol
• Lack of DAML rules
• Required for distributed trust policies.

4
JHU

• WHAT'S HOT?
• Search on DAML, text, or both
• Normalized DAML tags are used as indexing terms.
  Queries may include DAML, text, or both.
• Automated relevance feedback adds related words
  and DAML tags to the user's query. System finds
  DAML tags or words most closely related to a
  given word, phrase, or DAML tag.
• Ontology mapping
• Given a node in an ontology, system finds other
  DAML tags and words that characterize it, then
  finds other ontology nodes that have similar
  characterizations.
• Provides a simple ontology mapping capability.

• CHALLENGES!
• DAML quantity
• There is still not very much DAML on the Web
• DAML quality
• Monolithic files many DAML statements are
  concentrated in a few large files
• Structured database nature many DAML tags always
  co-occur with exactly the same set of tags,
  making it difficult to distinguish the tags
  statistically
• Is DAML markup? much DAML has very few
  accompanying words

5
MIT Sloan

• CHALLENGES!
• Heterogeneity of commercial rule languages, yet
  need deep common semantics
• potential de facto standards jockeying by vendors
• Multiplicity of protocols for procedural
  invocation
• CGI, SOAP, RMI, CORBA, ...
• Unordered (RDF) vs. ordered (XML) graph semantics
  for Webized syntax
• Little theory available for tight composition of
  Rules plus Description Logic -- yet want deep
  combined knowledge representation semantics
• Current gulf to databases/XMLQuery
  sociologically technically unconnected

• WHAT'S HOT?
• Webizing and extending logic programs
• Web-powerful URI's for relations, functions,
  rulesets, reasoning
• Web-friendly syntax exploit/support both XML
  and RDF, use namespaces
• Ontologies basic connection link ontologies for
  rules, and vice versa
• Object-oriented basic features subclass ...
  with exceptions member roles
• Infrastructure for inter-site communication of
  premises and conclusions (justifications)
• inferencing as a web service, with ...
• translation among rule languages
• merging web-named/accessible rulesets with
  prioritized conflict handling
• hybrid reasoning algorithms semantics
• Applications describe contracts and web
  services as rulesets and decide to buy/choose or
  sell via inferencing about the deal

6
Papers

1. X. Luan, Y. Peng, and T. Finin, Agent Consumer
   Reports of the Agents, by the Agents, and for
   the Agents, 2nd Asia-Pacific Conference on
   Intelligent Agent Technology, Maebashi City,
   Japan, Oct, 2001.
2. T. Finin, A. Joshi, L. Kagal, O. Ratsimore, V.
   Korolev, and H. Chen, Information Agents for
   Mobile and Embedded Devices, 5th Int. Workshop on
   Cooperative Information Agents, Sept. 6-8, 2001
   Modena, Italy.
3. L. Kagal, T. Finin, and Y. Peng, A Framework for
   Distributed Trust, Workshop on Autonomy,
   Delegation, and Control Interacting with
   Autonomous Agents, IJCAI-2001, Seattle, Aug.
   2001.
4. R. S. Cost, T. Finin, A. Joshi, Y. Peng, F.
   Perich, C. Nicholas, H. Chen, L. Kagal, Y. Zou,
   and S. Tolia, ITTALKS A Case Student in how the
   Semantic Web Helps, Semantic Web Workshop, July
   2001, Stanford.
5. F. Perich, R.S. Cost, T. Finin, A. Joshi, Y.
   Peng, C. Nicholas, H. Chen, L. Kagal, Y. Zou, and
   S. Tolia, ITTALKS An Application of Agents in
   the Semantic Web, Workshop on Engineering
   Societies in the Agents' World, 7 July 2001,
   Prague.
6. S. Avancha, A. Joshi and T. Finin, Enhancing
   Bluetooth Service Discovery Protocol, Report
   TR-CS-01-08, CSEE, UMBC, June 2001.
7. L. Kagal, Scott Cost, H. Chen, T. Finin, Yun
   Peng, An Infrastructure for Distributed Trust
   Management, Workshop on Norms and Institutions in
   Multiagent Systems, Autonomous Agents 2001,
   Montreal, May 2001.