1. 1 ITTALKS ITTALKS A Case Study in How DAML Helps Tim Finin University of Maryland Baltimore County Semantic Web for the Military User June 6, 2001 ask-all advertisesubscribe tell recommend register

2. 2 Overview 1.ITTALKS web application 2.Two advanced capabilities 3.How does DAML help? 4.Whats needed to build apps? Joint work with JHU/APL and MIT/Sloan. See http://umbc.edu/~finin/swmu/ for slideshttp://umbc.edu/~finin/swmu/

3. 3 UMBC/JHU/MIT DAML Project UMBC, JHU, and MIT are working together on a set of issues under funding from DARPA UMBC (Finin, et. al.) is focused on integrating communicating agents, DAML and the Web JHU APL (Mayfield, et. al.) is building information indexing and retrieval systems that work with documents and queries that contain a mixture of free text, XML and DAML MIT Sloan School (Grosof et. al.) is developing techniques for integrating rule based technology and distributed belief into DAML To be integrated in agent-based applications involving search and using rule-based reasoning.

4. 4 ITTALKS ITTALKS is a database driven web site of IT related talks at UMBC and other institutions. The database contains information on –Seminar events –People (speakers, hosts, users, …) –Places (rooms, institutions, …) This database is used to dynamically generate web pages and DAML descriptions for the talks and related information and serves as a focal point for agent-based services relating to these talks. We are exploring how the semantic web and DAML add value to this web-based application http://ittalks.org/ 1

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6. 6 Registered users create a profile (encoded in DAML) to describe their preferences and attributes.

7. 7 After logging in, ITTALKS can filter the talks shown based on my interests, schedule and location.

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10. 10 ITTALKS Architecture Web server + Java servlets DAML reasoning engine DAML files Agents Databases People RDBMS DB Email, HTML, SMS, WAP FIPA ACL, KQML, DAML SQL HTTP, KQML, DAML, Prolog MapBlast, CiteSeer, Google, … HTTP HTTP, WebScraping Web Services Apache Tomcat

11. 11 ITTALKS Ontologies Weve defined and use the following ontologies, all at http://daml.umbc.edu/ontologies/http://daml.umbc.edu/ontologies –calendar-ont.daml – calendar and schedule infocalendar-ont.daml –classification.daml – ACM CCS topicsclassification.daml –person-ont.daml – people and their attributesperson-ont.daml –place-ont.daml – talk locationsplace-ont.daml –profile-ont.daml – user modeling infoprofile-ont.daml –talk-ont.daml – talks infotalk-ont.daml –topic-ont.daml – topics and intereststopic-ont.daml

12. 12 ITTALKS Features Generation from DB to DAML and HTML mediated by MySQL, Java servlets, and JSP. Generation of DAML descriptions and user profiles from HTML forms. Creation & use of DAML-encoded user models describing interests and ontology extensions. Ontologies for events, people, places, schedules, topics, etc. Automatic HTML form (pre) filling from DAML. Syncing of talks with Palm calendars via Coola. Automatic classification of talks into topic ontology A XSB-based DAML/RDF reasoning engine. ITTALKS agent with KQML API using DAML as content language Intelligent matching of people and talks based on interests, locations and schedules. Agents using both Jackal and FIPAs Java Message Service Notification via email and mobile devices via SMS and WML. Discovery of relevant background papers from NEC CiteSeer Automatic generation and maintenance of user models Talk recommendations via collaborative filtering Integration with STP (Smart Things and Places) ubiquitous computing project Agent-based features General features

13. 13 Two Advanced Capabilities Ill briefly describe two advanced capabilities facilitated by DAML: –Classifying talk topics and user interests using DAML ontologies –Using DAML as a communication language among software agents 2

14. 14 Entering talks Currently, talks manually entered through a web form interface Several things help: (i) recognizing entities, e.g. people) already in the database and (ii) text classification Goal: become for research talks what NEC CiteSeer is for research papersNEC CiteSeer –Focused search engine to collect talk announcements in text or HTML or marked up in a partially understood ontology. –Information extraction using LMCOs Aerotext to extract relevant talk parameters and enter into databaseAerotext

15. 15 What are talks about? Topic hierarchies provide indexing terms –ACM CCS topic hierarchyACM CCS –Open DirectoryOpen Directory Encoded as DAML ontologies These allow users to specify interests as well as browse the database of talks by topic Automatic classification of talks (based on title and abstract) and users (based on his web pages, CV, papers, etc.) Discovery of mapping rules between CCS to OD ontologies using IR techniques

16. 16 Classifying Talks ACM CCS Ontology Training corpus CMU Bow statistical Bow text analysis tools CMU Bow statistical Bow text analysis tools ACM CCS classifier Now is the time for all good men to come to the aid of the country. Now is the time for topics e.g.: ACM CCS e.g.:5K ACM abstracts Topics Ontology uses

17. 17 Mapping between topic ontologies Topic ontology T1 Training corpus T1 CMU Bow statistical Bow text analysis tools CMU Bow statistical Bow text analysis tools T1 T2 mapper {(t2:bar, 0.8), (t2:qux, 0.7), …} Topic ontology T2 Training corpus T2 T1 T2 t1:foo

18. 18 DAML and Agents Much multi-agent systems work is grounded in Agent Communication Languages (e.g., KQML, FIPA) and associated software infrastructure such as the DARPA GridKQMLFIPADARPA Grid –The paradigm has been peer-to-peer message oriented communication mediated by brokers and facilitators. The DAML program invites different paradigms which will require some changes in ACLs and their associates software systems. –Agents publish beliefs, requests, and other speech acts on web pages. –Agents discover what peers have published on the web. The software agent research community is very interested in the semantic web and DAML ask-all advertisesubscribe

19. 19 ITTALKS Agent ITTALKS offers a web interface for its human users and can send notifications to humans via email, WAP and SMS. We are also developing an agent API so that software agents can interact with ITTALKS. Currently, the ITTALKS agent can send notifications to agents via KQML using DAML as the content language. –We will support richer, mixed initiative dialogs between ITTALKS and agents in the future

20. 20 ITTALKS agent Travel agent Calendar agent User agent DAML reasoning engine Broker Agent Agent Name Server users daml profile mapquest users calendar app ITTALKS app DAML reasoner Common agent infrastructure KQML API Communication protocol 1 8 76 5 3 2 4 9 10 11 12 13 17 16 15 14 18

21. 21 How Does DAML Help? Does it Help? Yes –Weve identified five general areas in which DAML adds value to the application or facilitates building or maintaining the application Is DAML needed? No –Not strictly (yet), although the alternative technologies are not designed for the web and thus suffer from deficiencies. 3

22. 22 How does DAML Help? ontology language user models interop language agent communication web services

23. 23 ontology language user models interop language agent communication web services Information in ITTALKS is exposed or published in DAML on the web. DAMLs descendant will become the semantic interlingua for applications and systems

24. 24 ontology language user models interop language agent communication web services DAML is used As a DB conceptual schema language To help specify APIs To aid human understanding

25. 25 ontology language user models interop language agent communication web services DAML is used to encode a common user model that Are stored in the users file space Contain information which can be shared by many applications Can contain information specific to certain applications

26. 26 ontology language user models interop language agent communication web services DAML is used to support agent communication as a content language used to encode the content of a KQML message Future: as an encoding for an entire FIPA ACL message and as a way of publishing speech acts on web pages

27. 27 Whats needed to build apps? Where does SW markup come from? –From Databases, just like much of the HTML on todays web –But, where does the DB content come from? From legacy systems From web forms or custom HCIs From focused search engines feeding into web scrapers or information extraction apps Are the DAML tools there? –Some in beta form –Many XML and RDF tools are very handy –We used protégé and XMLSpy to create and edit ontologies 4

28. 28 Conclusion ITTALKS is a useful, fairly sophisticated web application The semantic web concepts and DAML in particular –Make it easier to develop and maintain ITTALKS –Support some features of ITTALKS Visit http://ittalks.org/http://ittalks.org/ –To use ITTALKS –For more information, including a paper, a demo movie, and these slides mailto:info@ittalks.org to request a domain for your organization.mailto:info@ittalks.org

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