An Ontology-based Web-portal for Tourism Eleni Tomai 1, Stavros Michael 2,3, and Poulicos Prastacos 1,3 1 FORTH, Institute of Applied and Computational Mathematics Heraklion, Greece {etomai, poulicos}@iacm.forth.gr http://www.iacm.forth.gr/regional 2 Computer Science Department, University of Crete michael@csd.uoc.gr http://www.csd.uoc.gr/ 3 InfoCharta Ltd http://www.infocharta.gr Abstract. Traditional trip planning involves decisions made by tourists in order to explore an environment, such as a geographic area, usually without having any prior knowledge or experience with it. Contemporary technological development has facilitated not only human mobility but also has set the path for various applications to assist tourists in way-finding, event notification using location-based services etc. Our approach explores how the use of ontologies, in a web-based environment can be used for tourism applications. The methodology consists of building two separate ontologies, one for the users profile and another one concerning tourism information and data in order to assist visitors of an area plan their visit. 1 Introduction This paper draws from previous work on trip planning in the context of web services. Tourists present a special category of agents since they are on the move, they are very different from each other, have diverse interests and more importantly they are eager to explore an area for which we assume they have little prior information or knowledge. Several approaches have been presented, most of which making use of locationbased services and mobile technologies, which provide services for tourists. In [10] and [11], the need for user profiles in location-based services is explored. While in [9] the use of a context-aware system integrated in a mobile application is proposed for assisting tourists. Finally, in [5] a mobile system is introduced that offers guided tours using a semantic matching algorithm. The system previously proposed [7] is governed by the following concepts: since tourisms are not a group with homogeneous characteristics, the notion of personalization is crucial in the design of a decision support web service that helps them plan a trip. In [2] the development of Personalized Information Systems in a web environ-
ment is discussed in order to handle the plethora of available data on the web. Another important issue is that of context, referring to the usability/ conformity of the system s answer to the user as a result. To be more specific we have proposed a web service that can answer to the following types of questions: 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. In order to provide an answer, the system includes a conceptual model of the user profile. This is achieved by presenting to the user a questionnaire through a web based interface, so that the user s personal information, preferences, needs and interests can be extracted and recorded in a user profile ontology. The other dimension of the system is the tourism ontology that contains actual information on a specific area of interest. We have created a case study ontology for the prefecture of Heraklion, in the island of Crete, that we present herein. Although it is applied to Heraklion, a similar ontology can be applied elsewhere as well. Herein we concentrate on the two ontologies and what issues they address, what notions have been taken into account when building them and we present the progress of the system s implementation phase thus far. The remainder of the paper is constructed as follows: section 2 sketches the system architecture in its final version. While section 3 details the user profile ontology along with the user interface (which can be at the moment found on the web, and section 4 presents the ontology concerning tourism information. The context-matching algorithm, which will generate the mapping between the above mentioned ontologies, is roughly presented in section 5, this part is not detailed since we have not finished the previous stages. Finally, section 6 demonstrates further research challenges. 2 System Architecture This section presents the components of the system. These consist of the two ontologies, namely the user profile and the tourism ontology, the web-based user interface, the context matching algorithm and the map server. Starting with the two ontologies, their main difference is that the user profile ontology is elicited by the users responses to the interface while the tourism ontology is predefined. However, not even the procedure of the user profile generation is entirely free. On the contrary, this is done according to a predefined generic ontology, which facilitates the elicitation process and guides to a certain extent- the personalization of the system. Furthermore, the user profile ontology gets populated as more users utilize the system. The predefined ontology will be thoroughly presented and explained in section 3. On the other hand, the tourist ontology is populated in advance by the service provider, with real data, and only when he/she wants to update/expand the included information he/she can add more instances to the ontology. The main dimensions of the tourism ontology and how data is organized therein are explained in section 4. Apart from the two ontologies, in direct contact with the user is the interface for eliciting the user s characteristics. The interface poses ontology-driven queries to
elicit information concerning the user. The terminology used in the interface is in accordance with the terminology used in the user profile ontology (non-populated at first). The answers of the user are recorded by the system and included in the user profile ontology as its instance that has properties (characteristics) with specific values. A more detailed presentation of the interface can also be found in section 3. the interface is operational on the web at this point of the implementation phase. Another important component of the system is a map server, which shows the location of the tourism ontology s concepts of interest. In addition, the map server is utilized to visualize the answer of the system, so that the proposed places and itineraries are portrayed to the user. The system provides an answer to the query of the user using a context matching algorithm that matches the user profile to the tourism ontology, so that the answer given, matches user needs and interests. The functions of the algorithm are presented in section 5. The characteristics of the algorithm and its ability to generate mappings between the two ontologies, guarantee the conformity of the answer. The system works in two steps: first, the user fills in the interface so that his/her profile is generated, second the user states the question. Then, the system runs the context matching algorithm between the two ontologies and returns the answer as a text but also locating the proposed places/ points of interest on the map (fig. 1 shows the system architecture, and the procedure). context matching algorithm ontology No1: user profile user s profile user s question ontology No2: tourism Fig. 1. The architecture of the system 3 User Profile Ontology and Interface This section presents in detail the characteristics of the user profile ontology. The ontology was implemented using Protégé 3.0 [4] in OWL DL and its consistency tested using the RACE reasoner. The user profile ontology was created in order to facilitate the extraction of the user personal information, needs, and interests, under the context of personalization.
3.1 Personalizing the System The key characteristic of the ontology is that it is comprised of two steps. The first step, that of the design, concerns agreeing upon the main concepts of the ontology along with their properties. We have included in the ontology not only these concepts that characterize/describe a tourist but also concepts that account for the personal information of the user with respect to his/her trip making. To be more specific we included in the ontology concepts such as: age, gender, profession, leisure activities and interests, which sketch upon the personality of the user. Furthermore, concepts such as kind of trip, time available, temporal period of the visit, accompanying persons, money to spend, transportation means were added in order to reveal the characteristics of the user as a traveling agent. These 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 complete list of concepts of the user profile ontology is shown in fig. 2). Based on each concept, a corresponding property was created. To make this clear to the reader, from the concept interests, the property is interested in can be created which is assigned to the user and the values the property takes can all be found in the sub-concepts of the original concept, which is interests in this case. The properties of the ontology in this case play the role of posing questions to the user as a means to elicit to information from him/her. This functionality assists us in designing the user interface as it will be explained in the following section. 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 complete list of attributes, which are assigned to the user, is shown in fig. 3. Fig. 2. The concepts of the user profile ontology
Fig. 3. The properties of the user profile ontology, which are all, assigned to the user/ tourist, and their ranges 3.2 Populating the User Profile Ontology The second step is to populate the ontology with instances for the concept user. This is achieved, by providing an interface to the user so that he/she user can introduce
personal information, interests and facts about the visit. The interface resembles a questionnaire and, as previously mentioned, it is web-based. The procedure of collecting and recording the actual user profiles, in our case, is very much guided by the predefined user profile ontology. For example, when the user is asked to fill in his/her interests, he/she can only chose form a list of alternatives, given in the form of a drop-down menu, that correspond to the sub-concepts of the interests concept in the generic user profile ontology, presented earlier. This methodology has been previously presented in [6], for the creation of a web-based ontology editor. Figs. 4, 5 and 6 present the sequence of the interface s screenshots. The last step of the interface generates the owl file of the user, which in fact is a small fragment of the owl file of the generic user profile ontology (Fig. 7). This generated owl file is used in the context matching algorithm along with the tourism ontology to provide an answer to the end-user. Fig 4. The first screenshot of the interface, where the user is asked to fill in personal data
Fig 5. The second screenshot of the interface, where the user is asked to fill in what they are interested in and they like doing Fig 6. The third screenshot of the interface, where the user is asked to fill in their visiting conditions Fig 7. The generation of the owl file after submitting all the necessary information.
The qualities of this methodology are two fold: it can elicit information on the user profile using the same terminology as the one of the generic user profile ontology, and in addition, because the interface is structured based on the generic ontology; any information introduced therein can easily be recorded into the ontology as its instance (fig. 8). It can be easily understood that as more tourists use the system, the more the ontology gets populated. As a drawback, however, it should be pointed out that if the concepts of the generic ontology are modified, certain elements/pages of the interface should change to match the ontology. This downside really boils down to the adequacy and completeness of the original design of the ontology, which should minimize the risk of frequent changes. Fig. 8. An instance of a user in the user profile ontology 4 Ontology of Tourism This section describes the second core component of the system, that of the tourism ontology. This encompasses concepts familiar to all tourists such as sightseeing, shopping, leisure activities etc (fig. 9). The division of these fundamental concepts into sub-concepts, as those shown in fig. 9, was guided by the information of different websites and the classification of point of interest for tourists used therein such as the web pages of the city of Heraklion [3], the tourist guide for the municipality of Heraklion [8] and the agro-tourism site for Heraklion [1], available only in Greek. On the other hand, the concepts of location and time needed have central role in the ontology. The former refers to either the location a point of interest has on a map, or its address, if that kind of information is available, or even a text description, while the latter 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 (the reference point for all users is taken to be the centre of the city of Heraklion). Fig. 10 shows an example of locating a
Point of Interest using a map, because the address is not available (the POI refers to a plateau). Fig. 10. An example of how the location of a point of interest is defined in the tourism ontology Other concepts in the ontology concern additional information for the fundamental tourism concepts such as accessibility, entrance fees, opening hours and the like. Fig. 11 shows all the additional concepts included in the ontology. From those, we assign properties to the concepts of fig. 9. For instance, from the concepts accessibility we create the property; are accessed by which involves the sub-concepts of transportation, and the concepts which are assigned 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. Fig. 12 demonstrates the list of the properties of the concepts included in the tourism ontology.
Fig. 9. The core concepts of the tourism ontology
Fig. 11. The additional concepts of the tourism ontology that help us assign properties to the concepts of fig. 9 Fig. 12. The properties of the tourism ontology The tourism ontology is hidden form the user and it is populated with actual data as instances of the concepts included therein. This ontology was also implemented in Protégé in OWL DL. 5 Context Matching Algorithm One of the basic points in the approach described above is the service that makes the semantic matching, e.g. a service discovery mechanism that can give results with high precision according to the user s queries. In location-based services, the matching process involves the context, the user profile and the user history. We propose a web service that can take into account existing parameters in LBS environment although the user is in a certain and static place when querying the system s database. To overcome problems emerging by the lack of user under way, we prompt him to give us information about the context by filling up a questionnaire. For example, questions like: what is the time period you are visiting the X town?, give the system an overview of the user profile. As far as the location of the user is concerned our system works under the assumption that he/she is the city centre of Heraklion so all answers from the system concerning distance are measured from that point of reference. When 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. The second step involves finding the correspondences between concepts and properties in the user profile and those in the tourism ontology. The use of common terminology in both ontologies speeds up the matching process and makes it easier.
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, while in the last step, the matching result is classified in two modes; exact and approximate. Regardless the fact that the system finds a perfect matching or not, it is also able to give imperfect resulting sets as possible alternatives close to user s needs, the same approach has been proposed in [10]. In our approach, the user profile ontology is quite general in the sense that it has been designed in a way so that the corresponding interface which records all user information does not request from them detailed information for his/her interests or tastes. This design decision was taken on the basis that we wanted to provide to the users a list of alternative answers and let them take the final decision on how to spend their time. Another reason for keeping the user profile ontology quite generic is that our system does not tackle the issue of user history, therefore we needed to let the system give alternative answers on the assumption that it might not be the user s first time in Heraklion, consequently, a list of possible answers covers that aspect. Crucial feature of the specific algorithm is the calculation of time. As already mentioned in the tourism ontology the concept of time (time needed) t n 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. While in the user profile ontology time (time available) t a reflects the available time the tourist has to spend in Heraklion. Therefore if the time needed to visit a place of interest (t n1 ) is less than the time available of the user (t a ) the system incorporates in the answer another point of interest that has time needed to visit it (t n2 ). This process can go on as long as: n i t < t a, where i to n are the points of interest (1) n For the equation to give more sophisticated results the concept of proximity should also be incorporated in the algorithm, which accounts for how close several points of interest are. Another concept, which should be included in the algorithm when calculating time is that of transportation means. It is obvious that t n changes whether the user has a car or he/she uses public transportation. From this discussion, the calculation of time is quite critical for the conformity of the system s answer to the user needs. 6 Discussion and Further Work Several approaches have been proposed with the intension of helping tourisms in exploring points of interest in a usually unknown geographic area. Most approaches use location-based services and event notification methods in mobile system. Our approach however, presents novelties such as the following: 1. The system is not a mobile service but a web service provided by a local authority, such as the Greek ministry of tourism, the municipality of Heraklion etc.
2. The information concerning tourist activities (data) are organized in an ontology not separate databases, so that the schema is quite generic, it can be expanded (further include more information). 3. Our main contribution is the interface where the user inputs his/her personal information so that the ontology of the user profile is elicited. 4. Moreover, the terminology used in the interface is conformant to the terminology of the data ontology so that the matching algorithm is easier to implement and provide better results. We are actually at the point of populating the tourism ontology with actual data. Issues of data availability, accuracy, and maintenance are our top concern now. This will be the most time-consuming step of the implementation phase. All the abovementioned issues will influence the result of the procedure; the answer that the system will provide to the users. Further work concerns the testing of the system with the actual implementation of the context-matching. As a research question we will seek the inclusion of more parameters into the algorithm involving not only time available by the user, but also the amount of money he/she affords to spend during the visit. References 1. Agro-tourism site for the municipality of Heraklion: http://www.in.gr/agro/iraklio/nom1.htm 2. Galant V., Paprzycki M.: Information Personalization in an Internet Based Travel Support System. In: Abramowicz (ed.), Proceedings of the BIS'2002 Conference, Poland (2002) 191-202 3. Heraklion city s web pages: http://www.heraklion-city.gr/ 4. Protégé Ontology Editor (2004) http://protege.stanford.edu/ 5. ten Hagen K., Kramer R., Hermkes M., Schumann B., Mueller P.: Semantic Matching and Heuristic Search for a Dynamic Tour Guide, 12th International Conference on Information Technology and Travel & Tourism, Austria (2005) 6. Tomai E., Spanaki M.: From Ontology Design to Ontology Implementation: a Web Tool for Building Geographic Ontologies. In Toppen F., Painho M. (eds.): Proceedings of AGILE 2005, 8 th Conference on Geographic Information Science, ISEGI-UNL, Portugal (2005) 281-290 7. Tomai E. Spanaki M., Poulicos Prastacos, Kavouras M. Ontology assisted decision making - a case study in trip planning for tourism, International Workshop on Semantic-based Geographical Information Systems (SeBGIS'05), Cyprus, November 3-4, 2005 8. Tourist guide for Heraklion: http://www.4crete.gr/creteguide/en_heraklion.htm 9. van Setten M., Pokraev S., Koolwaaij J.: Context-Aware Recommendations in the Mobile Tourist Application COMPASS. Lecture Notes in Computer Science, Vol. 3137 (2004) 235-244 10. Yu S., Al-Jadir L., Spaccapietra S.: Matching User's Semantics with Data Semantics in Location-Based Services, 1st Workshop on Semantics in mobile Environments, Cyprus (2005) 11. Yu S., Spaccapietra, S., Cullot, N., Aufaure M.: User Profiles in Location-based Services: Make Humans More Nomadic and Personalised, Proceedings of the International Conference on Databases and Applications, Austria (2004)