1. Recognition and Satisfaction of Constraints in Free-Form Task Specification Muhammed Al-Muhammed

2. June 13, 20052 Motivation Semantic web promises automated tools to do tasks The challenge: how ordinary users deliver tasks to these tools Free-form text specification is a routine practice

3. June 13, 20053 Thesis Statement We can recognize required information and constraints in a free-form text task specification We can transform the satisfiability into a satisfaction of a database query

4. June 13, 20054 Approach Task ontology  Domain ontology  Process ontology Characteristics  Request recognition: find best task ontology  Recognize the required information and the imposed constraints  Transform their satisfaction into a regular data base query satisfaction The required information become SELECT part of the query The constraints become WHERE part of the query

5. June 13, 20055 Domain Ontology

6. June 13, 20056 Domain Ontology Augmented with data frames A data frame defines information about a concept  Its internal and external representation  Its contextual keywords or phrases  Operations along with contextual keywords or phrases

7. June 13, 20057 Data Frames Time … textual representation: “([2-9]|1[012]?)\s* :\s*([0-5]\d)\s*[AaPp]\s* \.?\s* [Mm]\s* \.?)” … end Distance internal representation: real textual representation: ((\d+(\.\d+)?)|(\.\d+)) context keywords/phrases: miles | mile | kilometers | … Within(d1: Distance, d2: Distance) returns (Boolean) contextual keywords/phrases: less than |  | … … end

8. June 13, 20058 Process Ontology A domain-independent process to handle the recognition and satisfaction of the constraints Statenet  States  Transitions, based on ECA rules Can be specialized to a domain

9. June 13, 20059 Task Ontology Recognition Appointment … context keywords/phrase: “appointment |want to see a |…” Dermatologist … context keywords/phrases: “([D|d]ermatologist) | …” I want to see a dermatologist next week; any day would be ok for me, at 4:00 p.m. The dermatologist must be within 20 miles from my home and must accept my insurance.

10. June 13, 200510 Task Ontology Recognition Appointment … context keywords/phrase: “appointment |want to see a |…” Dermatologist … context keywords/phrases: “([D|d]ermatologist) | …” I want to see a dermatologist next week; any day would be ok for me, at 4:00 p.m. The dermatologist must be within 20 miles from my home and must accept my insurance.

11. June 13, 200511 Task Ontology Recognition Appointment … context keywords/phrase: “appointment |want to see a |…” Dermatologist … context keywords/phrases: “([D|d]ermatologist) | …” I want to see a dermatologist next week; any day would be ok for me, at 4:00 p.m. The dermatologist must be within 20 miles from my home and must accept my insurance.

12. June 13, 200512 Task Ontology Recognition I want to see a dermatologist next week; any day would be ok for me, at 4:00 p.m. The dermatologist must be within 20 miles from my home and must accept my insurance. Date … NextWeek(d1: Date, d2: Date) returns (Boolean) context keywords/phrases: next week | week from now | … Distance internal representation : real textual representation: ((\d+(\.\d+)?)|(\.\d+)) context keywords/phrases: miles | mile | kilometers | … LessThanOrEqual(d1: Distance, “20”) returns (Boolean) context keywords/phrases: within | not more than |  | … return (d1  d2) … end

13. June 13, 200513 Recognition of Required Information: Task View Required information  The Mandatory concepts w.r.t. the primary concept  Marked concepts Heuristic-baser reasoning to remove spurious objects  Conflict resolution heuristic  Isolated object heuristic I want to see a dermatologist next week; any day would be ok for me, at 4:00 p.m. The dermatologist must be within 20 miles from my home and must accept my insurance.

14. June 13, 200514 Recognition of Required Information: Task View

15. June 13, 200515 Recognition of the Constraints Potential constraints are the marked Boolean operations  NextWeek(d: Date)  LessThanOrEqual(d1: Distance, “20”)  LessThan(d1: Distance, “20”)  Time = “4:00”  … Heuristic-based reasoning to remove the spurious constraints  Subsumption heuristic  …

16. June 13, 200516 Recognition of the Constraints Dependency graphs to capture dependency between  Constraints  Input parameters and the task view NextWeek LessThanOrEqual d1: Distance “20” DistanceBetween a1: Address a2: Address d: Date

17. June 13, 200517 Satisfaction of the Constraints Querying the database SELECT D.Name, D.Insurance, D.Address, A.Date, A.Time FROM Dermatologist D, Appointment A WHERE Time=“4:00” and NextWeek(Date) Observe that the constraint LessThanOrEqual(.,.) cannot be checked: need values from the user The remaining values are the model of the constraints NextWeek LessThanOrEqual d1: Distance “20” DistanceBetween a1: Address a2: Address d: Date

18. June 13, 200518 Contributions Recognition required information and imposed constraints in free-form task specifications Transform the constraints satisfaction to database query satisfaction Recognizing and gathering missing information from databases and users