Resolving Underconstrained and Overconstrained Systems of Conjunctive Constraints for Service Requests

Abstract

Abstract. Given a service request such as scheduling an appointment or purchasing a product, it is possible that the invocation of the service results in too many solutions that all satisfy the constraints of the request or in no solution that satisfies all the constraints. When the invocation results in too many solutions or no solution, a resolution process becomes necessary for agreeing on one of the solutions or finding some agreeable resolution. We address this problem by imposing an ordering over all solutions and over all near solutions. This ordering provides a way to select the best-m with dominated solutions or dominated near solutions eliminated. Further, we provide an expectation-based resolution process that can take the initiative and either elicit additional constraints or suggest which constraints should be relaxed. Experiments with our prototype implementation show that this resolution process correlates substantially with human behavior and thus can be effective in helping users reach an acceptable resolution for their service requests.

Ontology-Based Constraint Recognition for Free-Form Service Requests

“…We intend to conduct a user study to evaluate the performance of our augmented system. Second, we plan to integrate the work reported here with other work we have done [1] to produce the overall system we have envisioned [2]. The system we have envisioned transforms a service request into a predicate-calculus formula as explained here.…”

“…The system recognizes the constraints in a service request by two-fold process. (1) It matches a free-form service request against a collection of ontologies that belong to different domains to find the ontology that matches best. (2) It then selects from the given and implied constraints in the matched ontology those that are relevant to the service request to generate the constraints.…”

“…Examples include scheduling appointments, buying and selling products, renting apartments, setting up meetings, and many more. 1 Further, our initial work is for handling free-form service requests with conjunctive constraints. Therefore, our system in its current state does not handle service requests with negated constraints such as "not at 1:00 PM," disjunctive constraints such as "at 10:00 AM or after 3:00 PM," and conditional constraints such as "if the appointment can be next week, schedule me with Dr. Carter; otherwise with Dr.…”

Bringing Web Principles to Services: Ontology-BasedWeb Services

“…The OBWS, nevertheless, can use its ontology to provide default values for object sets. 1 For our example the OBWS provides To service a request, an OBWS must instantiate its output data instances by retriving them from its database or by computing them from other available data instances. For our example, the OBWS retrieves from its database values for MaximumTemperature, MinimumTemperature, and PercentChanceOfPrecipitation.…”

“…A service that can appropriately respond observes the posting and responds. The response is twofold: (1) it highlights the part of the query it "understands" (weather, tomorrow, and Springfield, Illinois in Figure 2) and (2) it answers the query (MaximumTemperature=70, MinimumTemperature=38, and PercentChanceOfPrecipitation=10 in Figure 2). …”