J. Software Engineering & Applications, 2010, 3, 776-783
doi:10.4236/jsea.2010.38090 Published Online August 2010 (http://www.SciRP.org/journal/jsea)
Applications of Norm and Situation Calculus in the
Semantic Web Service Composition*
Jun Zhao1, Xiaoz hu Gu2
1School of Economics and Management, Ningxia University, Yinchuan, China; 2School of Mathematical and Computer Sciences,
Ningxia University, Yinchuan, China.
Received June 23rd 2010; revised July 8th 2010; accepted July 24th 2010.
ABSTRACT
Semantic Web service studies are carried out around the OWL-S, however, OWL-S model does not contain the descrip-
tion of preferences and co nstraints when we ch oose and use them in differen t organization s, different cultures, different
sectors and actors because of OWL capacity limitations in rules. It means that Semantic Web service composition can
not compose users’ subjective services from the user requirements. The paper makes up for the semantic shortcoming of
OWL-S through using norm semantic sca lability, and achieves th e formal de scription of the norm by us ing the situa tion
calculus. Finally, the paper also takes a tourism composite service as an example how to extend the ability of the se-
mantic description of OWL-S, which shows us the combination of the norm and the situation calculus. It is positive sig-
nificance for even tually realizing semantic extension of OWL-S.
Keywords: Norm, Situation Calculus, Web Service, Semantic Web, Web Service Composition
1. Introduction
Web services are described using WSDL, but WSDL
only from the syntactic layer of the Web service descrip-
tion. It does not support the rich semantic descriptions.
Semantic Web can be regarded as an extension and ex-
pansion of the current Web technology. Web services are
an increasingly important resource of web, it require se-
mantic to provide wide range semantic support. OWL-S
is bridges to connect Web services and semantic Web.
Many of the current research on semantic Web services
are carried around the OWL-S. However, as the capacity
limitations of the rules of OWL, OWL-S model does not
include the description of preferences and constraints in
users’ selection and use of services, which always mani-
fests in the form of rules. The user's preferences and
scene constraints can’t be understood and processed well
by the computer because of the expression limitations. It
also means that intelligent system does not start from
user requirements during service composition, and does
not assemble more subjective service in accordance with
users’ will. Therefore, the article will extend the seman-
tic of OWL-S through semantic capabilities of the norm.
However, norm is non-formal and ambiguous. This paper
attempts to use situatio n calculus to formally describ e the
norm in order to ensure the correctness of norm and the
user correct expression of various scene constraints, and
provide more accurate and subjective service in expres-
sion of the preferences.
2. Related Researches
Sheila A. McIlraith, Srini Narayanan and others of Stan-
ford University apply the th eory of situation calculus and
Petri net to study the operational semantics of OWL-S.
Firstly, they study the conversion relationship between
the atomic service description and situation calculus.
Then, they use situation calculus to study the formal se-
mantics of atomic service descriptions in OWL-S. The
situation calculus as an intermediate language is con-
verted into the Petri net, and then the Petri net is used to
study the implementation reasoning of the operational
semantics of semantic Web services [1].
Andrea and Ferrara, who come from DIS-University di
Roma use an approach of the process algebra to study the
Web service composition, establish mutual mapping
between process algebra and Business Process Execution
Language for Web Services based on the research of
Srini Narayanan and others [2].
SWSI (Semantic Web Services Initiative), mainly by
DARPA and the EU (European Union) funded a project
to build a combination of Semantic Web and Web ser-
vices technology integration framework that enables ser-
*This research was supported by the Natural Science Foundation o
f
China (No. 70961 0 0 7).

Applications of Norm and Situatio n Calcu lus in the Semantic Web Service Composition 777
vice providers and service requesters in the service dis-
covery retrieval, matching, call, monitor and so on to
achieve the greatest possible integration of automation
and dynamic.
Yongshang Cheng and Zh ijian Wangf, who come fro m
College of Computer and Information Engineering, He-
hai University have invented formal model of semantic
Web services on the basis of colored Petri nets [3] .They
formally describes several basic web service composition
models in OWL-S, which is constructed to meet the de-
mand of service, but it lacks of the expression of services
semantic information.
Jun Liao, Hao Tan and Jinde Liu, who come from the
University of Electronic Science and Technology, de-
scribe the Web service composition by using Pi calculus.
The paper introduces an example using Pi calculus to
describe the Web service composition [4].
From the above research and projects we can see that
researchers have made some valuable results in the se-
mantic Web and Web service composition context, and
many research problems wait to be solved to provide
more powerful semantics services especially in the se-
mantic extensions, but the theoretical system of service
composition engineering and implementation technology
are still immature because the study of history is not
long.
This paper introduces norm theory of Organizational
Semiotics to solve th e problem of semantic deficiency in
Web service composition. In order to achieve a deeper
level of semantic extension, it achieves the formal de-
scription of norm in semantic expansion by the theory of
situation calculus in order to ensure the accuracy of se-
mantic extension.
3. Applications of Norm and Situation
Calculus in the Semantic Web Service
Composition
Norm is also known as social norms which is the com-
mon rules of conduct and standards of every member in a
social group or smaller groups, which is in the Oxford
Encyclopedia of the explanation.
As rules in expression limitations of the OWL,
OWL-S model does not include the users’ the description
of preferences and constraints in the selection and use of
services. It try to introduce norm to provides a new th eo-
retical platform in the se mantic Web service compositio n
in order to solve Web services Semantic shortage de-
scribed by the OWL-S in the semantic Web service
composition. This approach considers many the users’
initiative and willingness. It joins the human factor in the
service composition to provide a more personalized
composition services.
Norm determines whether and when an event occurs,
and also decided meeting the particular needs should call
the areas of service layer of what services. It can describe
the activities relationship of the system control. The
norm detailed description includ es the following sections
[5].
Whenever< Conditions set >If< State Sets >Then
<Agent>Is <Deontic Operator>To< Action sets >Con-
sequence< Result Sets>
Conditions Sets specified the conditions when an
Agent executed an act. Further instructions can be speci-
fied by If < State set>, which show that it happened in
what state. <Agent> Refers to the responsibility Agent,
Agent may be people here, also may be software. < De-
ontic logic operators> including allowing (Permitted),
must (Obliged), prohibition (Prohibited)etc. <Action
Sets> determined action sets applied in the case of cond i-
tions to met for Agent. <Result sets> is the results after
the successful implementation of the specification, which
is also the goals of users implement the act.
We can see that norm is different from the relations of
causality [6]. Causality is usually on ly a brief description,
if the conditions are met, then certain beh avior co uld take
place. Therefore causality is rigid and limited, and there
is not available for human decision. On the contrary,
norms are a better reflection of how people activities in
the business environment. Therefore it is more suited to
the description of user needs in the real business.
Changes of user needs in the growing environment can
be described through the norm. This required model can
fully focus on changes factors. It will help to provide
dynamically alternative solutions among the service layer
and process layer on us er needs.
Situation Calculus is a multi-type and first-order logic
language, and has some second-order characteristics. It is
a formal planning approach and describes a logical basis
for dynamic system. For problem solving of the dynamic
field and logic programming, it is first proposed in 1963
by McCarthy who is the master of artificial intelligence.
Goal-oriented autonomous behavior reasoning can be
carried out in a dynamic environment by situation calcu-
lus. In the situation calculus, a scenario is a snapshot of
the world, and dynamic changes in the world are all the
result of actions. Scenarios class is applied to express
Situation Calculu s, and the scene change is th e results of
the actions. In ontology, the action is the basic means to
change the state of things. Therefore, a possible world
active can be viewed as a string of action series. Situation
calculus constitutes by the following three elements: ac-
tion, situation and fl ow.
Action is the basic means to change station of things.
All Changes in the state of things are the result of the
implementation of the action sequences. A specific pre-
dicate Pos s is used to indicate that an action is executa-
ble.
Situation is the dynamic world. All changes in the
world are the result of action, which is a string of limited
action sequences. Action function is expressed as: action

Applications of Norm and Situatio n Calcu lus in the Semantic Web Service Composition 778
Table 1. Mapping norm to situation calculus
situationsituation. If the action a is implemented un-
der the scena rio s, th en anothe r situa tion will b e got, an d
the situation s can be expressed as do (a, s). Items of normItems of the situation calculus
Input Conditions Input Function (,)
K
refa s
Conditions set
State set
Action Precondition Axiom:
(,) i Possa sf
Obliged Desirable Axiom (,)
D
esirable a s
Permitted int( , )Constraa s

Prohibited Constraint Axiom int( , )Constraas
Action set Action predicate ( , )Possa s
Result Set Effect Axioms and Condition Output
Function:
(,)
K
whether as (,)
K
whether as
Flow is used to represent the properties of thin gs in the
world and the link between them [7]. When an action
occurs, the flow will change. Flow F(x, s) takes scene s
as its last parameter. The initial situation is expressed as
s0. The value of the flow is constantly changing from the
initial state of the world to the current world state.
In order to characterize the dynamic changing world,
situation calculus theory uses the following actions: Ac-
tion Precondition Axiom, Successor State Axiom, Effect
Axiom etc. [8].
Action Precondition Axiom: Every action of the field
has a corresponding action precondition axioms, de-
scribing a prerequisite for action to perform.
(,)i Poss asf i
f
is a prerequisite sets for the im-
plementation of. a4. Case Studies
4.1 Example Background
Successor State Axiom: Each flow in field has a corre-
sponding Successor State Axiom, which is described the
implementation of atomic actions how to affect the flow
and state changes.
Tourism is an integrated industry which includes food,
housing, transportation, travel, shopping and entertain-
ment. A trip involves a number of services and tourism
resources, and tourist information is rich in space and
time content. Travel is the complex process restricted by
artificial and natural factors. How to use Web services by
the network to provide “personal travel” service and how
to design personalized service process according to the
needs of our customers become a problem. The problem
has plagued further development of the tourism industry
and prevented from increasing the overall quality of
tourism services to increase tourists’ satisfaction. There-
fore the examples will make a combination of the weath-
er check, ticket booking, tourist attractions, reservations
and other travel services with personal characters. The
service composition flow is shown in Figure 1.
(,)(,,)(, (,))
F
Possasxas Fxdoas 


(,)(,,)(,(,))
F
Poss asxasFxdoa s 


(,)Poss a s is a special flow and action is en-
forceable under state
a
s
.
Formula (,,)
F
x
as 
 is a positive effect axiom that
describes the related collection of actions and conditions
to makes the value of flow
F
true after the execution.
Formula (,,)
F
x
as 
 is a negative effect axiom that de-
scribes the related collection of actions and conditions to
makes the value of flow
F
false after the execution.
In addition to the above several axioms, there are other
flows that can be used to describe atomic service or a
combination of services as formal semantics of services
in situation calculus. Other flows are the following types:
The example mainly involves the following web ser-
vices:
1) (, )
I
nquireWeather CityDate: Weather inquiry ser-
vice.
(,)
K
refa s expresses that the value of is known
under the scenario
a
s
. 2) tan (,)
I
nquireDisce StartDestination: Check the dis-
tance between the two places. Start is the place of depar-
ture. Destination is the sightseeing place.
(,)
K
whethera sexpresses that the true value of is
known under the scenario
a
s
. 3) : Booking airline
tickets.
(,BuyAirPlaneTicket CityDate)
)
)
)
(,)
K
nows as expresses that the function value of
is known under the scenario
a
s
. 4) : Booking train tickets.
(,BuyTrainTicket CityDate
This essay will introduce users Desirable Axiom and
constraint Axiom in order to express the will degree of
user requirements in the situation calculus [9-10]. We
also attempt to define which action
under the situation
int( , )Constraa s
a
s
can be implemented as long as
the users’ conditions are not limited [11].
5) : Attractions reservation.
(BookScenicSpots City
6) : Buy insurance. ()BookInsurance TypesOfInsurance
7) Re : Service of cars on hire. ( )ntCar CarModel
8) : Hotel reservation. (BookHotel City
A set of items compared norm expression with situa-
tion calculus to achieve the service semantic expansion
and formal description. It is shown as Table 1.
4.2 Norm Analysis
A detailed analysis of the norm is as below Tables 2-9.

Applications of Norm and Situatio n Calcu lus in the Semantic Web Service Composition 779
Figure 1. The chart of reservation service composition flow
Table 2. Weather norm
Norm 1 Searching start
In Charge of User
Information
Recognition City, Date
User query the weather of sightseeing site
Precondition: Enter valid city and date
Trigger
Condition Th en: Weather query service returns query results
Detailed
Norm
if the input date and destination of users a re
valid then Weather enquiry service is obliged
to return the query results
Table 3. Distance query norm
Norm 2 Searching start
In Charge of User
Information
Recognition Start, Destination
User queries the distan ce between the start
and destination
Precondition: The query results of norm 1 is sun
Trigger
Condition
Then: Return the distance between start
and destination
Detailed
Norm
Whenever the weather of the indicated Date is
sunny in norm1 if the input start and destination of
users are valid then distance query service is
obliged to return the distance between two places
Table 4. Airline reservation norm
Norm 3 Booking start
In Charge of User
Information
Recognition Bank Card ID, User ID
Users make flight reser vati on s
Precondition: Output is sunny in norm1and
the output is greater than or equal 1000
kilometers in norm 2
Trigger
Condition Then: Users input bank card password ,book
ticket
Detailed
Norm
Whenever Output is sunny in norm1and the
output is greater than or equal 1000 kilometers
in norm 2 if bank card ID and user ID are valid
then user is obliged to input bank card
password to transfer
Table 5. Train ticket reservation norm
Norm 4 Booking start
In Charge of User
Information
Recognition Bank Card ID ,User ID
Users book train tickets
Precondition: Output is sunny in norm1and the
output is greater than or equal 1000 k il ometers in
norm 2
Trigger
Condition
Then: Users input bank card password ,book ticket
Detailed
Norm
Whenever Output is sunny in norm 1and the
output is greater than or equal 1000 kilometers in
norm 2 if bank card ID and user ID are valid then
user permitted input bank card password to
transfer

Applications of Norm and Situatio n Calcu lus in the Semantic Web Service Composition 780
Table 6. Attractions reservation norm
Norm 5 Booking start
In Charge of User
Information
Recognition City
Users reserve scenic spot
Precondition: City is valid, the grade of
attractions are four A-leve l or above
Trigger
Condition
Then: Return the attrac tions which are qualified
Detailed
Norm
Whenever norn 3 and norm4 are success f u l if
the grade of attractions are four A-level or above
then users permitted input bank card
password and transfer reserve attractions if the
grade of attractions are below fou r A-level then
norm 3 or norm 4 is prohibited to book
Table 7. Insurance booking norm
Norm 6 Booking start
In Charge of User
Information
Recognition City
Users reserve insurance
Precondition: City is valid, user s c ho os e
appropriate insurance
Trigger
Condition Then: Users input the bank card password and
transfer; Users reserve insurance
Detailed
Norm
Whenever norm 3 or norm 4 are successful if
thegrade of attractions are four A-level or above
then user is obliged to input bank card
password and transfer in order to reserve
attraction
Table 8. Car rental reservation norm
Norm 7 Booking start
In Charge of User
Information
Recognition City
Users reserve the car which is rental
Precondition: City is valid, the rental car is
full-time
Trigger
Condition Then: Users input bank card password in order
to reserve rental cars
Detailed
Norm
Whenever norm 3 or n o rm 4,norm 5 , no r m 6
are successful if the rental car is full-time then
users is obliged to input bank car d pa s sw o rd
in order to reserve the rental car
Table 9. Hotel reservation norm
Norm 8 Booking start
In Charge of User
Information
Recognition Bank Card ID ,User ID
Users reserve hotel
Precondition: Norm 3 or n orm 4 and norm 5
norm 6 norm 7 are successful; The hotel is
three-star or above
Trigger
Condition
Then: Booking hotel
Detailed
Norm
Whenever Norm 3 or norm 4 a nd n orm 5
norm 6 norm 7 are successful if hotel is above
3A then user is obliged to input bank card
password in order to reserve hotels
4.3 Mapping from Norm to Situation Calculus
1) The Situation Calculus Formally Describes the Atomic
Services in Example
a) Weather atomic service: Before the atomic service
of Weather is implemented, agency must know the input
parameters value which is formalized as the following
formula with the situation calculus.
((,Poss InquireWeather City Dates),)
) (,)( ,
K
refCity sKrefDates

(, )
I
nquireWeather CityDate
ty Date
(,)
is a weather query action,
the action on the premise that you need to know the
and , which can be represented by flow
Ci
K
refCity s(, and )
K
refDate s.
Users want to travel as long as the weather was not
dust storms and heavy rain. It is formalized as the fol-
lowing formula with the situation calculus.
int(, )ConstraTranvel s


((,,WeatherEqualStorm s)


(, ,)WeatherEqualSadstorms );
,)
The output of the Weather Service is formalized as the
following formula with the situation calculus.
(,)(,Poss InquireWeather sx InquireWeather s


(/ ,(,))
K
nows SunOther do InquireWeathers
b) The atomic service of distance query: Before the
atomic service of Distance Query is implemented, agen-
cy must know the input parameters value which is for-
malized as the following formula with the situation cal-
culus. ((, ),)Poss Distance StartDestinations
(,) (,)
K
refStartsKrefDestinations

The output of the Distance Query Service is formal-
ized as the following formula with the situation calculus.
(tan,)(,tan,)Poss DiscesxDisces



( ,(tan,))
K
nowsFigure doDisce s
c) Ticket booking atomic services: Before the atomic
service of Airline Reservation is implemented, agency
must know the input parameters value which is formal-
ized as the following formula with the situation calculus.
((,PossBuyAirplaneTicket CityDates),)
)
(,)( ,
K
refCity sKrefDates

If user wants to buy air tickets must be that the dis-
tance between two places is greater than or equal to
1,000 kilometers. It is formalized as the following for-
mula with the situation calculus.
((,DesirableBuyAirplaneTicket CityDates),)

tan ((,),1000);DisceStart DestinatinLonger
The effectiveness and output parameters of atomic
service buy ticket are formalized as the following Posi-
tive Effect Axiom and Negative Effect Axiom.

Applications of Norm and Situatio n Calcu lus in the Semantic Web Service Composition 781
:(
FaBuyAirplaneTicket CityDate

,)
)
(,
I
nstockAirplaneTicket CityDate
(,)( ,)Poss asaBuyAirplaneTicket CityDate 
(, )
InstockAirplaneTicket CityDate
(,ownAirplaneTicketdoa s(,))
2) The Situation Calculus Formally describes the
Composition Services in Example
The Example involve several combination services:
is composed of the Distance Query Service,
ticket booking service and ticket reservation service,
which implement are controlled mainly by if control
operator;
BookTi cket
J
ourney is composed of the Attractions Res-
ervation Service; Insurance Booking Service and Car
Rental Reservation Service, which implement are con-
trolled mainly by
A
nyordered
Tranvel
BookTi cket
control operator; The
composition service is composed of the com-
position service; composition service
J
ourney and Hotel Reservation Service, which imple-
ment are controlled mainly by C control op-
erator. ondition
a) Composition service: Distance Query
Service, ticket booking service and ticket reservation
service is composed, which implement are
controlled mainly by control operator.
BookTi cket
okTicketBo
if
The prerequisite was formalized as the following for-
mula in the situation calculus:
((1000 ,
K
nows Overkm
(tan(,), ))do InquireDisceStartDestinations
((,PossBuyAirplaneTicket CityDates),)
(,((, ),)))Knows Sun doInquireWeather CityDates
((1000 ,
K
nows Belowkm
(tan(,), ))do InquireDisceStartDestinations
((,PossBuyTrainTicket CityDates),)
(,((,), )));
K
nows Sun do InquireWeather CityDates
Before the composition service of is im-
plemented, agency must know the input parameters value
which is formalized as the following formula with the
situation calculus.
BookTi cket
((1000 ,
K
nows Overkm
(tan(,), ))do InquireDisceStartDestinations
((,PossBuyAirplaneTicket CityDates),)
(,)( ,))KrefCity sKrefDates
((1000 ,
K
nows Belowkm
(tan(,), ))do InquireDisceStartDestinations
((,PossBuyTrainTicket CityDates),)
)
(,)( ,)
K
refCitysKrefDate s
Based on the above two formulas, we can get the Ac-
tion Precondition Axiom.
((1000 ,
K
nows Overkm
(tan(,), ))do InquireDisceStartDestinations

((,PossBuyAirplaneTicket CityDates),)
(,((, ),))Knows Sun doInquireWeather CityDates

(,)( ,))KrefCity sKrefDates


((1000 ,
K
nows Belowkm
(tan(,), ))do InquireDisceStartDestinations

((,PossBuyTrainTicket CityDates),)
(,((, ),))Knows Sun doInquireWeather CityDates

(,)( ,))
K
refCity sKrefDates

The effectiveness and output parameters of composi-
tion service are formalized as the following Positive Ef-
fect Axiom and Negative Effect Axiom.
1
:(
FaBuyAirplaneTicket City Date

,)


(, )
I
nstockAirplaneTicket CityDate
2(, )aBuyTrainTicket City Date


(, )
I
nstockTrainTicket CityDate
((1000 ,
K
nows Overkm
((,do InquireDistanceStartDestinations),))

11
(,) (,,)
F
Poss asxas 



1
(,(OwnAirplaneTicketdoas
((1000 ,
,)))
K
nows Belowkm
((,do InquireDistanceStartDestinations),))

22
(,) (,,)
F
Poss asx as 



2
(,(Own TrainTicketdo as ,)))
,)
1
:(
FaBuyAirplaneTicket CityDate




(,NoInstockAirplaneTicket CityDate)
2(, )aBuyTrainTicket CityDate


(,NoInstockTrainTicket CityDate
((1000 ,
)
K
nows Overkm
(tan(,), ))do InquireDisceStartDestinations

11
(,) (,,)
F
Poss asxas 



1
(,(OwnAirplaneTicketdo as,)))


((1000 ,
K
nows Belowkm
(tan(,), ))do InquireDisceStartDestinations

22
(,) (,,)
F
Poss asx as 



2
(,(, )))Own TrainTicketdo as

The output of the Composition Service
was formalized as the following formula with the situa-
tion calculus.
BookTi cket
((1000 ,
K
nows Overkm

Applications of Norm and Situatio n Calcu lus in the Semantic Web Service Composition 782
(tan(,), ))do InquireDisceStartDestinations
11
(,) (,,)Possa sxa s


1
(,(, )))KnowsAirplaneTicketMessagedo as
((1000 ,
K
nows Belowkm
(tan(,), ))do InquireDisceStartDestinations
22
(,) (,,)Possa sxa s


2
(,(,)))
K
nows TrainTicketMessagedoas
b) Composition service
J
ourney : It is composed with
Attractions Reservation Service, Insurance Booking Ser-
vice and Car Rental Reservation Service. Implement of
the service is controlled by
A
nyordered control opera-
tor.
The implementation order of atomic services which
are involved in the composition service is not required,
so the composition service can be controlled imple-
mented
A
nyordered control operator.
The prerequisite was formalized as the following for-
mula with the situation calculus.
((PossBookScenicSpotsCitys),)
),
))
)))
((PossBookInsurance TypesOfInsurance
(,do BookScenicSpots s
(Re (),
PossntCar CarModel
(,(,do BookInsurancedo BookScenicSpots s
(,
K
nows GreaterFourA(,do InquireScenicSpots s))

(,
K
nows TypesOfInsurance
((doInquireInsurance TypesOfInsurances,)))

(,(Re,Knows CarModeldoInquirentCars))
),
),
))
(Re(), )PossntCar CarModels
((PossBookInsurance TypesOfInsurance
(Re, ))dontCar s((PossBookScenicSpots City
(,(Re, )))doBookInsurance dontCars
(,(Re,Knows CarModeldoInquirentCars
(,
K
nows TypesOfInsurance
((doInquireInsurance TypesOfInsurances,)))

(,( ,))
K
nowsGreaterFourA doInquireScenicSpotss
Before the composition service of
J
ourney is im-
plemented, the agency must know the input parameters
value which is formalized as the following formula with
the situation calculus.
((PossBookScenicSpotsCitys),)
),
))
((PossBookInsurance TypesOfInsurance
(,do BookScenicSpots s
(Re(), (,PossntCar CarModeldo BookInsurance
(, )))do BookScenicSpots s
(,) (,)
K
refCitysKrefTypesOfInsurance s
(,)
K
refCarModel s(Re(),)PossntCar CarModels

((PossBookInsurance TypesOfInsurance),
(Re, ))dontCar s

((PossBookScenicSpots City),
)
(,(Re, )))doBookInsurance dontCars
(,)(,
K
refCarModelsKrefTypesOfInsurance s


(,)
K
refCity s
The above two formulas, we can get the Action Pre-
condition Axiom.
((PossBookScenicSpotsCitys),)
),
))
((PossBookInsurance TypesOfInsurance
(,do BookScenicSpotss

(Re(), (,PossntCar CarModeldo BookInsurance
(, )))do BookScenicSpots s
(,(Knows GreaterFourA doInquireScenicSpotss,))

(,
K
nows TypesOfInsurance
((doInquireInsurance TypesOfInsurances,)))

(,(Re,Knows CarModeldoInquirentCars))

(,) (,)
K
refCitysKrefTypesOfInsurance s


(,)
K
refCarModel s(Re(),)PossntCar CarModels

((PossBookInsurance TypesOfInsurance),
(Re, ))dontCar s

((PossBookScenicSpots City),
))
(,(Re, )))doBookInsurance dontCars
(,(Re,Knows CarModeldoInquirentCars

(,
K
nows TypesOfInsurance
((doInquireInsurance TypesOfInsurances,)))

(,(Knows GreaterFourA doInquireScenicSpotss,))

(,)
K
refCarModel s

(,)(,)
K
refTypesOfInsurance sKrefCitys
In this combination of services, users require the at-
tractions level to be 4A or above and the rental car is
full-time on behalf of driving, the above can be mapped
to the Desirable Axiom with the situation calculus.
((DesirableBookScenicSpots Citys), )
Grade(, )GreaterFourA s
(Re(), )DesirablentCar CarModels
Re(, )ntCarModel WholeDays
The composition service is composed of the
composition service. Composition service
Tranvel
icketBookT
J
ourney
Condition
and Hotel Reservation Service are controlled by
control operator.
Here the ,
BookTi cket
J
ourney and Hotel Reservation
service are seen as the three actions: ,
1
a BookTicket
2
aJourney

, 3 a BookHotel

.
1
a and are the implementation precondition of
2
a

Applications of Norm and Situatio n Calcu lus in the Semantic Web Service Composition 783
)
3
a, the implementation of composition service Travel
can be controlled by the control operator.
Condition
(ookTicket s
(,ourney s
,(
The prerequisite of composition service was
formalized as the following formula in the situation cal-
culus.
Travel
(, ,)Knows Success do B
3
(, ))(,)Knows Success doJPoss as
(3 ,))
K
nows GreaterStardotelsoInquireH
(ookTicket s
(,ourney s
Before the composition service of is imple-
mented, the agency must know the input parameters
value which is formalized as the following formula with
the situation calculus.
Travel
(, ,)Knows Success do B)
)
3
(, ))(,)Knows Success doJPoss as
(,
K
refCity s
The above two formulas, we can get the Action Pre-
condition Axiom.
(, ,)Knows Success do B(ookTicket s
(,ourney s
( 3
)

3
(, ))(,)Knows Success doJPoss as
(,),(,))
K
refCity sKnowsdo InquireHotGreater Star
)City Instock
(ookTicket s
(,ourney s
,) s
3
(do as
(ookTicket s
(,ourney s
)
el s
The effectiveness and output parameters of composi-
tion service are formalized as the following Positive Ef-
fect Axiom and Negative Effect Axiom.
3
:((
Fa BookHotelRoom

)
)
)
,))
)
)
(, ,)Knows Success do B
(, )Knows Success doJ
33
(,) (,
F
Poss asxa 

(,OwnTanvelMessage
The output of the Composition Service was formalized
as the following formula with the situation calculus.
(, ,)Knows Success do B
(, )Knows Success doJ
33
(,) (,,Possa sxa s


3
(, (,))
K
nows TanvelMessagedoas
5. Summary
This paper introduces the norm to strengthen the seman-
tics from user needs perspective based on the defects of
lack of semantics described in OWL-S semantic service
of the semantic web service composition. A new way is
provided to increase semantic. However, the norm is
non-formal and ambiguous, the situation calculus is ap-
plied to realize formal norm in order to ensure the accu-
racy of semantic Web service composition.
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