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Semantic Web Services 191
phases of web service composition. It is important to know that not each real problem can
be described and solved using planning. Examples are environments where the future state
can not be determined before it is reached. For instance, the n-body problem belongs into
this category. It deals with the finding of motions of n bodies determined by Newton’s
laws of motion and Newton’s law of gravity. The first contribution to the solution of n-
body problem has been done by Poincaré in 1892 [40]. The first version of his contribution
contained an error, described in [34]. The problem was finally solved by Karl Fritiof Sundman
(for n =3) [42]. The result is that it is not possible to solve the n-body problem analytically.
Only numerical methods can be used to find a solution with arbitrary precision (greater than
zero). Consider a planning problem where we want to the fly to Mars and land on an exactly
specified point. The existence of the n-body problem proves that there can not be found
a plan which solves this problem.
The subset of problems solvable by planning techniques is restricted. Consider all
domains solvable using a common computer, more precisely by a Turing machine with
final tape. These domains are also solvable using a STRIPS-like or HTN-like planners, whose
expressiveness is equivalent [49]. Hence, the set of problems which can be solved by planning
is restricted at least to this domain. Based on the concrete technique used, other restrictions
can occur.
Now we focus on more concrete problems we must deal with in Semantic web service
composition. The first problem of the utilization of web service composition appears already
at the first step. This is how to gather information about the initial situation and the goal state
from the user. The web service composition methods already work with specific formalisms
like OWL-S. Descriptions in these languages can not be directly obtained from the user.
Different user-computer interactions can take place here.
One example of a user interaction tool is described in [56, 57]. The gathering of the
information is based on context detection. The context was detected based on user’s textual
input of a note. A tool EMBET analyzes this input and finds relation between parts of this
note and ontological concepts. After this a list of context suggestions are presented to a user
who can select the relevant ones. Based on the context, those services which are closely
related to it are suggested to be those producing the desired output for the user.
Another approach to gathering information about the user’s goal is presented in [71].
The described system is a smartphone interface to the Semantic web – SmartWeb. It constitutes
from a PDA client, dialog server, and the Semantic web access system. In the PDA client
a Java-based control unite takes care about the inputs and outputs. The dialog server includes
modules for speech interpretation, natural language generation, and user context detection.
The Semantic web access system contains modules for question-answering sub-system, semantic
web service composer, semantic web pages, and knowledge server. The aim of the
system is to make the Semantic web accessible for the user in convenient way. It assists the
user during finding information taking into account its context and exploiting also Semantic
web services. When web service composition is required, the system generates questions to
acquire the necessary information for construction and execution of the composite service.
It is not clear if the approach used in SmartWeb is sufficient to be used universally and
how dependent it is on the domain. Very important role in this system plays the ontological
knowledge base. Building a sufficiently large, consistent ontology which can be effectively
processed by machines still presents a problem. Automatic approaches using for example