Dwipa Search Engine: When E-Tourism Meets The Semantic Web Guson Prasamuarso Kuntarto, Dennis Gunawan Department of Information System and Computer Science Universitas Bakrie and Universitas Multimedia Nusantara Email:
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Abstract—Internet is an important component in technology development, including tourism. Tourism is an industry which involves much information needed for traveling. Many tourists search for travel information in the web. Nevertheless, the web often gives irrelevant information. Besides that, a huge size of information in the web and the spread of the information in many different sources make users need more time in searching for information and organizing them from many different sources manually. Semantic web is a solution to solve those problems by providing knowledge based on an ontology. E-tourism is a good domain for implementing the semantic web because there are many information sources and data exchange involved in the etourism. In this paper, a knowledge base which is based on an ontology is designed and built using Protégé tool version 3.4.7. The ontology consists of tourism domainspecific information and stores data of accommodation, attraction, and cultural event in Bali which is one of the main travel destinations in Indonesia. Besides that, a search engine application for e-tourism in Bali, which implements the semantic web, is designed and built using RAP-RDF version 0.9.6 and RDF query language: SPARQL so that the search results conform to the ontology. Keywords— Semantic Web, Ontology, Knowledge Base, Search Engine, E-Tourism
I. INTRODUCTION The Internet technology grows rapidly, including in developing countries. According to Internet World Stats [1], there were 39,600,000 Internet users in Indonesia in December 2010. Internet has changed daily lifestyle and business activities. Web, which grows significantly, becomes a need for modern society to make transactions, search the information, and spread the information. Although web can give all information needed, it often gives irrelevant information to the user [2]. In addition, because of the huge size of information in the web and the spread of information in many different sources, users have to spend more time in searching and integrating the information manually from those sources [2].
Internet has an inseparable role in technology development, including tourism [3]. Tourism is an industry which brings in revenue for many countries, including Indonesia. In 2010, Indonesia’s income from tourism sector reached US$ 7,603.45 and there were 7,002,944 foreign tourists who visit Indonesia [4]. Tourism is considered to be the most appropriate domain to implement the semantic web because it involves a lot of information sources and data exchange [5]. Bali is one of the main tourist destination in Indonesia, especially for foreign tourists. In 2008, the number of tourists who came to Ngurah Rai airport increased 26.1% [6]. In 2010, foreign tourists who visited Bali as the main destination in Indonesia increased about 11.5% compared to the same period in 2009 [7]. However, search engine application based on the semantic web still relatively hasn’t been developed, whereas this technology offers ease in obtaining information, such as accommodation, attraction, and cultural event by utilizing the ontology or knowledge [8]. Challenges and pressures from the tourism industry, companies and consumers to stimulate the development of semantic web technologies [14]. II. RELATED WORKS According Wellem problems E-Tourism in Indonesia are very similar in Europe. The problem is that websites supporting the tourism industry such as shipping, airlines, hotels, travel agencies and tourism managers are not yet integrated. E-Toursim in Indonesia only as a medium of display information in the form of text or image, without any interactive communication between industries supporting tourism [10]. Implementation of Semantic Web technologies can help tourism information sharing and enable interoperability of information between industry pengukung tourism [9]. Wellem managed to build an ontology specific to tourism in Bali, which consists of data supporting the tourism industry such as hotels, attractions and more. The ontology is used as the semantic web technology information center [10]. Dema has designed and implemented a Knowledge Based (KB) consisting of tourism domain-specific
information. KB stores facts about Bhutan, which are structured by an ontology. KB also uses to store facts according to its partonomy rules that encode the geographical partitioning. Rajkumar, Gohin, and Vinod have been managed to create an ontology for promoting e-tourism. research conducted is to measure the similarity of the results entered by the user input system to generate data relevant tourism from a web service [12]. Soza A. M., Garrido L. C. T.V from the publication in 2010, they have managed to develop a web ontology in order to support tourism sector in Colombian Caribbean. Mistilis states on the publication in 2012, that challenges faced by the tourism industry and the semantic web technology is the primary standard of data to be applied or realized. The role of ontologies start at initialization by providing standard concepts and language in order to connect the two challenges [14]. III. APPLICATION DESIGN A. Semantic Web Model Observation is carried out on the web of accommodations, events, and attractions in Bali to obtain the tourism data. The data collected from the observation consists of 28 accommodations, 108 attractions, 7 events, and 9 regencies. The data is used to build the ontology using Protégé tool. The ontology is used to model the knowledge domain. In the adaptive system, a user model is used to represent users (customers) and an adaptation model is defined. The adaptation model uses knowledge from the ontology to generate a personalized output based on the initialized user model which represents customers behavior to the interface. The output generated is suggestions of accommodation, attraction, and cultural event in Bali based on the customer needs. The output becomes a parameter to perform testing. The semantic web model is illustrated in Fig 1.
class, Accommodation class, and Regency class. The Attraction class consists of 12 subclasses which are the types of attraction in Bali: Waterbom, TraditionalArtMarket, ArtVillages, HistoricalBuilding, Lake, DivingAndSnorkelling, Surfing, Rafting, Ecotourism, Watersport, Museum, and Temple. The Event class has 4 subclasses which are the types of event in Bali: Annually, Monthly, Weekly, and Daily. The Accommodation class and Regency class don’t have any subclass. The Class Attraction, Events, Accommodation, and the Regency have properties that connect a class with another class. Class Suites have Properties hasAccommodation, hasAttraction, and hasEvent, which stores an instance of another class which is the third accommodation, attractions, and events in the district. Class Accommodation has hasAccommodationRegency property, which is the inverse of the property hasAccommodation, which stores an instance of the class Regency which is the county where the accommodation is located. Class of Attraction has hasAttractionRegency property, which is the inverse of the property hasAttraction, which stores an instance of the class Regency which is the district where the attraction is located. Class Event has hasEventRegency property, which is the inverse of the property hasEvent, which stores an instance of the class Regency which is the county where the event took place. The class structure of object properties in the ontology for e-tourism Bali can be seen in Fig 3
Fig 2. Object Properties’s structure on Dwipa’s Ontology
Based on Fig 2, the notation for object properties on the ontology can be drawn as mentioned on Fig 3 below. Fig 1. Semantic Web Model for E-Tourism in Bali
B. Ontology Ontology construction is an improvement over the built ontology Wellem with an outlook from Rajkumar and Soza works. Ontology generated in this study was constructed based approach to ontology structure subpart of a country, especially Indonesia. In general, usually composed of Indonesia, provincial, district / city and district as did Dema on Buthan. But keep supporting data of the tourism industry such as hotels, tourism and others as has been done by Wellem. The ontology consists of 4 classes: Attraction class, Event
Fig 3. Notation for Object Properties on Dwipa’s Ontology
C. Search Engine Application When users open the search engine application, users are directed to the home / index page. Users can go to another page by clicking on the link which directs users to the page chosen. If it is the accommodation, attraction, and event page, users have to input the search criteria. The accommodation search
criteria consist of the regency where the accommodation is located in, room rates per night, and the facilities provided in the accommodation. The attraction search criteria consist of the regency where the attraction is located in and the type of the attraction. The event search criteria consist of the regency where the event takes place, the type of the event, and the day or date when the event is held. The search engine searches the information on the ontology named etourismbali.owl. After the search process is completed, the result is shown to the users. The flowchart of the search engine is illustrated in Fig 4. Unlike traditional search engines perform comparative text with web documents, based searches using the domain ontology as the set of a concept will generate consistent search criteria the user on one or more domain information [13]. The following design of search engine (Dwipa) is used ontology for the base of searching.
Fig 5. Search Engine’s Interface
Fig 6. Example of Search Engine’s Result for Accomodation
IV. IMPLEMENTATION A. Attraction Search Query for searching the attraction based on attraction type and regency in Bali is shown in Fig 7.
Fig 4. Search Engine Flowchart
D. User Interface Users have to input the search criteria by choosing the search criteria, such as the regency, room rates per night, type of attraction, type of event, and the day or date when the event is held, in a combo box. On the accommodation page, the facilities are grouped into six categories: general, health and body treatment, cultural activities, other activities, transportation, and sports. The facilities are grouped using jQuery accordion and users can choose the facilities by ticking the check box in front of each facility they want to choose. To start the search process, users have to click the search button at the bottom of the search page. The user interface of the search engine is shown in Fig 5. After the search button is clicked, the search engine performs the search process and returns the results to the user. As an example, Fig 6 shows the results for the accommodation search which consist of the accommodation image, name, address, phone number, fax number, and email address.
Fig 7. Query for Attraction Search
B. Event Search If the type of event searched by user is a weekly event, the search process is carried out based on the regency where the event takes place and the day when the event is held. Query for searching the weekly event is shown in Fig 8.
Fig 8. Query for Weekly Event Search
If the type of event searched by user is an annual event or a monthly event, the search process is carried out based on the regency where the event takes place and the date when the event is held. Query for searching the annual and monthly event is shown in Fig 9.
Accommodation pages are built according to design accommodation page design phase. The process of finding accommodation on this page returns the search results according to the ontology.
Fig 9. Query for Annual and Monthly Event Search
If the type of event searched by user is a daily event, the search process is carried out based on the regency where the event takes place. Query for searching the daily event is shown in Fig 10.
Fig 10. Query for Daily Event Search
C. Accomodation Search Firstly, the search engine searches the accommodations which have the facilities selected by the user. The query for searching the accommodations based on the facilities selected by the user is shown in Fig 11.
Fig 11. Query for Accommodation Search Based on Facilities
Each facility selected by the user is appended to the query (see Fig 12).
Fig 12. Appending Facilities to the Query
After all facilities selected by the user are appended to the query, the query is terminated with ‘}’ (a right curly bracket), as shown in Fig 12.
Fig 12. Query Termination with ‘}’
For every result of the query execution, the accommodation data, which are literals and consist of name, address, phone number, fax number, and email address, are processed to get the information which can be used for the next query. The process is shown in Fig 13.
Fig 13. Accommodation Data Processing
After the process is finished, the accommodation search is carried out based on selected room rates per night. For every result of the previous query execution, the room rates per night is obtained using a query, as shown in Fig 14.
Fig 14. Query for Obtaining Room Rates
If one of the room rates in the accommodation equals to the selected room rates, the accommodation information which consist of name, address, phone number, fax number, and email address are stored into an array (see Fig 15). Afterward, the information are shown to the user. V. DISCUSSION Dwipa has been tested on the server located at http:// http://123.231.xxx.xxx/ which has Intel Xeon CPU E5540 @2.53GHz processor and 4096MB RAM. The server uses Windows Server Enterprise (6.0, Build 6001) operating system and Apache 2.0 web server. The ontology named etourism.owl represents 44 accomodations all across Bali, 8 major attractions, 8 major events including weekly, monthly and yearly events. In the testing phase, the search engine was tested using 50 queries which consist of 25 queries for accommodation, 20 queries for attraction, and 5 queries for event. The search results conform to the ontology
This is indicated by the similarity of the results of the expected output and the output on the web browser. TABLE I THE SEARCHING ACCOMODATION RESULTS
TABLE II THE SEARCHING ATTRACTION RESULTS
Fig 15. Process of Storing Accommodation Information
However, there is a drawback on the FILTER feature in the RAP framework. It doesn’t recognize ‘>’ operator. Although it recognizes ‘
