International Workshop on Semantic Based GIS Ontology assisted decision making a case study in trip planning for tourism Eleni Tomai, Maria Spanaki, Poulicos

International Workshop on Semantic Based GIS

Ontology assisted decision makinga case study in trip planning for tourism

Eleni Tomai, Maria Spanaki, Poulicos Prastacos and Marinos Kavouras

National Technical University of Athens, Cartography Laboratory, & FORTH, Institute of Applied and Computational Mathematics


Outline

Objective

System Architecture

Ontologies

Context Matching Algorithm

General Discussion


Objective

Trip planning in the context of web services. Tourists are not a group with homogeneous

characteristics, therefore personalization is crucial in the design of a decision support web service.

Develop a web service that can answer to the following types of questions/requests: I have two days to spend in X, what do you

propose me to do? Today I want to do some sightseeing in X and

then go to sea.


System Architecture - I

contextmatchingalgorithm

user’s profile

user’s question

ontology No1: user

profile

ontology No2:

tourism


System Architecture - II

It consists of: The two ontologies, namely user profile and tourism

ontology, implemented using OWL Plug-in of Protégé. The web-based user interface, which poses ontology-driven

queries to elicit information concerning the user. The context matching algorithm which matches the user

profile to the tourism ontology. The map server which shows the location of the tourism

ontology’s concepts of interest, it is also utilized to visualize the answer of the system.

The system works in two steps: 1. the user fills in the interface to generate a profile, and then

states the question. 2. the system runs the context matching algorithm and returns

the answer.


The Ontologies User Profile Ontology I

1. The design, concerns agreeing upon the main concepts of the ontology along with their properties.

concepts that characterize/ describe a tourist (e.g. kind of trip, time available, temporal period of the visit, accompanying persons, money to spend, transportation means)

concepts that account for the personal information of the user (such as: age, gender, profession, leisure activities, interests).

The concepts were further detailed by adding sub-concepts; for instance, for the concept leisure activities the sub-concepts eating out, nightlife, shopping and sports were created.



The Ontologies User Profile Ontology II Based on each concept, a corresponding property was

created. For instance, from the concept interests, the property

is interested in can be created assigned to the user. The properties of the ontology play the role of posing

questions to the user as a means to elicit to information from him/her.

For the previous example a question is: what are you interested in? And a possible answer from the user is: I am interested in museums.



The Ontologies User Profile Ontology III

2. The second step is to populate the ontology with instances for the concept user.

Provide an interface to the user so that he/she can introduce personal information, interests and facts about the visit. The interface “resembles” a questionnaire and, it is web-based.The procedure of collecting and recording the actual user profiles, is very much guided by the predefined user profile ontology. When the user is asked to fill in his/her interests,

he/she can only chose from a list of alternatives, given in the questionnaire, that correspond to the sub-concepts of the interests concept in the generic user profile ontology.



The Ontologies User Profile Ontology IV

The qualities of this methodology are two fold:1. it elicits information on the user profile using the

same terminology as the one of the generic user profile ontology, and

2. because the interface is structured based on the generic ontology; any information introduced therein can easily be recorded into the ontology as its instance.

As more tourists use the system, the more the ontology gets populated.

Possible drawback: if the concepts of the generic ontology are modified, certain elements/pages of the interface should change to match the ontology.



The Ontologies Ontology of Tourism I It includes concepts such as sightseeing, shopping, leisure

activities etc. The concepts of location and time needed have central role

in the ontology.

Location refers to either the location a point of interest has on a map, or its address, if that kind of information is available.

Time refers to the time it takes for the tourist to get to the point of interest plus the average time to see the place and come back.

Other concepts in the ontology concern additional information such as accessibility, entrance fees, opening hours and the like.

(Has been implemented for the region of Heraklion, Crete.)



The Ontologies Ontology of Tourism II Assigning properties to the concepts.

For instance, from the concept accessibility we create the property; are accessed by which involves the sub-concept of transportation, and the concepts which are assigned with this property are: archaeological sites, museums, natural beauty areas etc.

Properties help us set statements such as the following: archaeological sites are accessed by busses,

or beaches are accessed by taxis and ferries etc.

The tourism ontology is hidden from the user and it is populated with actual data as instances of the concepts included therein.



Context Matching Algorithm I

How it works:1. The user queries the system according to his/her

interests and the time to spend, the semantic matching process starts by filtering out the services that do not match the service types asked by the user.

2. The second step involves finding the correspondences between concepts and properties in the user profile and those in the tourism ontology.

3. On the third step, additional information provided by the user such as visiting period is taken into account and narrows even more the initial query.

As for the location of the user, the system works under the assumption that they are in the city centre of Heraklion.


Context Matching Algorithm II Provides to the users a list of alternative answers and let

them make the final decision on how to spend their time. Crucial feature of the specific algorithm is the calculation

of time. In the tourism ontology the concept of time (time

needed -tn) encodes the time it takes for the tourist to get to a point of interest from the centre of Heraklion plus the average time to see the place and come back to the centre.

In the user profile ontology time (time available -ta) reflects the available time the tourist has to spend in Heraklion.

The concept of proximity should also be incorporated in the algorithm.

Another concept which should be taken into account is transportation means.


General Discussion and Future Trends

Several approaches have been proposed with the intension of helping tourisms in exploring points of interest.

Our approach presents novelties such as the following: The system is not a mobile service but a web service

provided by a local authority. The information concerning tourist activities (data) is

organized in an ontology not separate databases. The interface where the user inputs his/her personal

information so that the ontology of the user profile is elicited and gradually populated.

The terminology used in the interface is conformant to the terminology of the user profile ontology.

Further work concerns the inclusion of more parameters into the context matching algorithm.

Moreover, several issues concerning the accuracy and availability of data should be investigated.

Documents

International Workshop on Semantic Based GIS Ontology assisted decision making a case study in trip planning for tourism Eleni Tomai, Maria Spanaki, Poulicos