1. CS621 : Artificial Intelligence Pushpak Bhattacharyya CSE Dept., IIT Bombay Lecture 12 RDF, OWL, Minimax

2. RDF recap

3. Fundamental Triple E.g., And so on

4. Namespace Give meaning to a name Specifically, bind a name with an URI (uniform resource identifier in the web) Pushpak http://www.cse.iitb.ac.in/~pb {person} Pushpak http://www.imdb.com/title/tt0251355/ {movie}

5. Draw the names from the namespace I just got a new pet dog.

6. RDF: Resource Description Format Each RDF statement has three parts: a subject, a predicate and an object Makes statements about resources on the web, uniquely identified by URIs

7. Example (from W3C specification of RDF) In natural Language http://www.example.org/index.html has a creator whose value is John Smith http://www.example.org/index.html has a creation-date whose value is August 16, 1999 http://www.example.org/index.html has a language whose value is English

8. Subject-Predicate-Object based scheme the subject is the URL http://www.example.org/index.html the predicate is the word "creator" the object is the phrase "John Smith"

9. More concretely through URIs a subject http://www.example.org/index.html a predicate http://purl.org/dc/elements/1.1/creator and an object http://www.example.org/staffid/85740

10. In graphical form

11. With all other information

12. In triple notation Subject http://www.example.org/index.html http://purl.org/dc/elements/1.1/creator> http://purl.org/dc/elements/1.1/creator http://www.example.org/staffid/85740 Predicate http://www.example.org/index.html "August 16, 1999". Object http://www.example.org/index.html http://purl.org/dc/elements/1.1/language "en".

13. Ontology

14. Building blocks Concepts Relationships instances

15. Taxonomic organization of knowledge

16. Simple Inference

17. Fundamental relationships Hypernymy Subclass (man mammal Membership (Ram ε man) Meronymy (part whole) (hand part-of body)

18. Languages for representing ontology RDF/RDFS DAML+OIL OWL

19. Systems for representing ontology Wordnet CYC UMLS

20. From National Library of Medicine Unified Medical Language System (UMLS®) to facilitate the development of computer systems that behave as if they "understand" the meaning of the language of biomedicine and health UMLS Knowledge Sources (databases) and associated software tools (programs) Systems that create, process, retrieve, integrate, and/or aggregate biomedical and health data and information patient records, scientific literature, guidelines, public health data

21. UMLS semantic n/w Major groupings of semantic types include organisms, anatomical structures, biologic function, chemicals, events, physical objects, and concepts or ideas. Is-a hierarchy Non-hierarchical relations:`physically related to,' `spatially related to,' `temporally related to,' `functionally related to,' and `conceptually related to.'

22. How is ontology used In IR: query expansion In expert systems: for generalization

23. Layering XML RDF Schemas and Ontologies User given tags and arbitrary structure Meaning Sharable and reusable information

24. Spectrum of ontologies Amount of meaning and formality increases left to right terms Data dictionaris thesauri XML DTD DB schema XML Schema Formal Taxonomy Frame Description Logic General Logic

25. Web ontology language OWL lite OWL DL OWL full

26. OWL (Web Ontology Language)

27. Structure of OWL document Name space http://www.w3.org/2002/07/owl# http://www.w3.org/2002/07/owl# Name Space name owl OWL header: version information, ontology comments, import statements, title, creator etc. Owl:imports used to import other ontologies

28. OWL classes OWL: Thing OWL: Nothing Classes named using URLs Anonymous classes possible

29. Class description as property restriction Value restrictions OWL: AllValuesFrom OWL: SomeValuesFrom OWL: hasValue Cardinality restrictions OWL: minCardinality OWL: maxCardinality OWL: cardinality

30. Value Restrictions 1) 2) 3) 2) 1) 2) 3) 1) 2) 3) Elective is an individual in the ontology

31. Cardinality Restrictions 1) 6 2) 1 3) 1

32. Complex classes Owl: Union Of Owl: IntersectionOf Owl: ComplementOf

33. Examples of Complex Classes: unionOf 1. 2. 3. 4. 2.

34. Examples of Complex Classes: intersectionOf 1. 2. 1. 2. 1 1.

35. Examples of Complex Classes: complementOf 1. 2.

36. Class Axioms: subclassOf 1. 2. 3.

37. Class Axioms: equivalentClass 1. 2. 3.

38. Class Axioms: disjointWith 1. 2. 3.

39. Other operations

40. Minimax with alpha-beta cut

41. An example search tree 8 7 2 6 5 4 3 9 8 7 S A B C D E F G HI J evaluations

42. Minimax with alpha-beta pruning (DFS)- step 1 9 8 7 S A D E F Backup=7

43. Minimax with alpha-beta pruning (DFS)- step 2 7 6 6 9 8 7 S A B D E F G H 5 Can only decrease Need not be generated 7

44. Minimax with alpha-beta pruning (DFS)- step 3 7 6 4 6 5 4 3 9 8 7 S A B C D E F G H I J 7 Need not be generated

45. An example in predicate calculus

46. A “department” environment 1. Dr. X is the HoD of CSE 2. Y and Z work in CSE 3. Dr. P is the HoD of ME 4. Q and R work in ME 5. Y is married to Q 6. By Institute policy staffs of the same department cannot marry 7. All married staff of CSE are insured by LIC 8. HoD is the boss of all staff in the department

47. Questions on “department” Who works on CSE? Is there a married person in ME? Is there somebody insured by LIC?