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(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 2, May 2010
Ontology Based Information Retrieval for
E-Tourism
G.Sudha Sadasivam C.Kavitha M.SaravanaPriya
Professor,Department of CSE Senior Lecturer PG Student
PSG College of Technology PSG College of Technology PSG College of Technology
Coimbatore,India Coimbatore, India Coimbatore, India
Email id: sudhasadhasivam@yahoo.com Email id:mail2kavithak@yahoo.com Email id:priyakut@gmail.com
Abstract - This paper reports work done in the E-Tourism agents to analyze the Web on our behalf, making smart
project. The overall goal of the project is to improve information inferences that go beyond the simple linguistic analysis
creation, maintenance and delivery in the tourism industry by performed by today’s search engines [5]. The applications that
introducing semantic technologies. This paper analyzes the deliver these new online solutions are based on ontology.
weakness of keyword based techniques and proposes need for
Ontology is basically a description of the key concepts in a
semantic based intelligent information retrieval for tourism
domain. The Semantic Web is an evolving development of the given domain including the rules, properties and relationships
World Wide Web in which the meaning of information and between concepts. There are many challenges involved in
services on the web is defined, making it possible for the web to implementing such an innovative new approach for online
understand and satisfy the requests of people and machines to search services. Ontology modeling and ontology based
use the web content. It also supports the transparent exchange of information retrieval are two of the major issues faced by
information and knowledge among collaborating e-business developers. In this paper, Ontology modeling tool Protégé and
organizations. It focuses meaningful exchange of knowledge an architecture based on the tool aimed at addressing these
between organizations. Major challenge faced by the semantic issues are presented. The paper proposes a convenient and
web application is modeling of ontology and ontology based
effective way for ontology engineer to create domain ontology
information retrieval. The software framework has been
developed using Protégé tool for Travels and Tourism domain. enables Ontology engineer to update the ontology by adding
This framework facilitates creation and maintenance of ontology. instances and deploys effective applications and facilitates
The paper also proposes two methods for information retrieval ontology based querying of Semantic Web resources.
namely top down and bottom up approach. A comparison of
these two approaches also presented in the paper. II. PROPOSED ARCHITECTURE
Keywords: Semantic Web, Keyword based Search Engine, Fig 1 represents a framework to support convenient and
Ontology, Protégé Tool, Jambalaya, Jena Agent. intelligent querying of Semantic Web resources for
information retrieval. The key role players of this architecture
include Admin, Ontology modeling tool Protégé and End user.
I. INTRODUCTION
A. Design Steps
When surfing on the Internet, end users are 1. The admin or ontology engineer creates ontology by using
increasingly in need of more powerful tools capable of protégé tool.
searching and interpreting the vast amount of heterogeneous 2. If any new activity is to be added to the ontology, the
information available on the Web. Current Web has been ontology needs to be updated. The ontology engineer updates
designed for direct human processing, but the next-generation the ontology by adding instances.
“Semantic Web,” aims at machine-process able 3. End user searches for web content in the same way as in a
information[8].The Semantic Web also provides the conventional search engine and issues requests using the
foundation for semantic architecture to support the transparent system’s GUI
exchange of information and knowledge among collaborating 4. The End users query to Jena agent and ontology will be
e-business organizations [2]. Recent advances in the Semantic traversed either top down or bottom up approach according to
Web technologies offer means for organizations to exchange end user specification
knowledge in a meaningful way [5]. The idea allows software 5. The Jena agent retrieves the query result and passes the
result to GUI.
78 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 2, May 2010
6. The GUI displays the results to the end user. end user selects the source name, destination name and
budget, then ontology will be traversed and meaningful result
will be displayed based on top down approach. If the end user
Specifies the restaurant name, accommodation name and
travels name then ontology will be traversed using bottom up
Jena Agent
approach
Protégé tool
IV IMPLEMENTATION DETAILS
Admin Protégé is used to model ontology. It is an open
Ontology Ontology source tool which is used to construct knowledge based
Creation updation application using ontology. Ontology is a formal explicit
specification of shared conceptualization. It provides a
platform for ontology engineers to create ontology and form
the ontology knowledge-base. The tool displays and edits
ontology in graphical mode, and can synchronously create
Ontology ontology OWL [6] files as well. The work of creating
ontology is realized by jambalya[9], Property Window,
Individual Editor Window. According to the outline view, all
the ontology objects and relative properties could be listed and
displayed. The multi-layer edit view comprises two parts
Ontology Traversal
namely Class edit view and Property edit view. The edit view
displays subclasses, instances, classes, inheritance and
equivalence, mapping relation between class and instance .The
edit view of Property displays properties, inheritance and
equivalence relation of properties
A. Tourism Domain Ontology Creation:
The Protégé tool is used to create Travels and
Query Result
Tourism domain ontology. Fig.2 displays Travels and Tourism
domain ontology created by Protégé tool using Jambalya. It
has travels and tourism ontology with Travels, Restaurant,
End-User
Accommodation, and Activity concepts for the cities like
Mumbai, Chennai, Delhi, Hyderabad, Kolkata and Bangalore.
Properties and relationship are set between each concept.
Instance is created for each concept and value is assigned for
Fig. 1 System Architecture
each instance. Class Editor Window enables the ontology
engineer to create and update the classes. Multiple siblings can
be created for a same class. Based on the need, the ontology
III PROPOSED METHODOLOGY engineer can set the restrictions and comment for each classes.
The ontology engineer can create a number of properties for a
A. Travels and Tourism class using property window. Property window includes two
types of properties namely Data type property, Object
The Travels and Tourism Recommendation System is a property. The data type property mentions the data type for
travel consultancy system designed to provide budget each property. The ontology engineer has to specify property
traveling details to customer. Although travel resources on the with corresponding subclass, range and allowable values for
internet are abundant, information is widely distributed among that property. The object poperty mentions the relationship
multiple travel agents. If end users want to gather information, between each class or concept. In the edit view of Property
they need to spend time searching on the internet. The results window, properties, inheritance and equivalence relation of
of the query are usually not accurate and sufficient. So it is properties are all displayed here. The ontology engineer
necessary to design Travels and Tourism Recommendation creates number of instances or individuals for each class or
System to help budget travelers to arrange their journey and concept and assign values for each instance based on data
budget [6]. In Tourism recommendation system, whenever the type property.
79 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 2, May 2010
C. Searching and Retrieval
In In Travels and Tourism Recommendation system, when
the end user issues requests the ontology will be traversed
using top down approach or bottom up approach
, when . 1) Top down Approach:
In this approach the end user has to specify the
source name, destination name and budget, according to
budget the ontology will be traversed and results will be
displayed to end user. It has 2 choices namely travel agency
choice and enduser choice.
a) Travel Agency Choice: Here the end user specifies
the source name, destination name and budget. The Travel
agency queries the end user for his preference namely Travels
or Tourism. If end user preference namely travels then details
of luxury travels are extracted. If the end user preference is
tourism details of tourist spots are extracted. According to end
users budget, travels and tourism ontology instance weight
Fig. 2 Travels and Tourism Ontology will be added. The sum of instance weight is which is less than
or equal to end user budget as results will be extracted and
B. Tourism Domain Ontology Updation
displayed.
The ontology engineer can update the ontology by
adding instances.
Fig. 4 Travel Agency choice
Fig 4 displays the searching result based on budget
Fig. 2 Ontology updation estimation, preference and distance between source and
destination. According to end user estimation and
Fig.3 displays the ontology updation dynamically during run
preference, the corresponding destination Tourist spots,
time. The ontology engineer has to specify the instance name
Restaurant, Accommodation and Travels details are
with corresponding concept name to which instance is to be
displayed based on sum of instance weight.
dynamically added. Finally ontology gets updated
80 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 2, May 2010
b) End User Choice: End users are also provided
with facilities to look over travels and tour spots. The end
users favorite’s travel, accommodation, restaurant, and tour
spot and wishes to visit it in future, can be marked as his
favorite spots. Fig 5 displays the information retrieval
according to end user specification. The end user has to
specify source name, destination name and budget category.
According to budget category (luxury or medium or
ordinary) the tourist spot, accommodation, restaurant and
travels details are extracted.
Fig. 6 Bottom up with travel agency choice
b) End User Choice: The Fig 7 displays bottom up
traversal with end user choice. Once the end user is provided
with all the instances based on his choice the system displays
destination, type and category of restaurant, accommodation
and travels.
Fig. 5 End User choice
2) Bottom up approach:
The bottom up approach is used to identify the location
and category of specified activity, accommodation name,
restaurant name that belong to the cities Mumbai, Chennai,
Delhi, Calcutta, Bombay are displayed. Choices are available
in this approach
a) Travel Agency Choice: The Fig 6 displays bottom
up traversal with travel agency choice. In this approach, the
travel agency queries to the end user for estimation. Based on
that estimation all the instances of the sub classes are Fig. 7 Bottom up with customer choice
restaurant, accommodation and travels are displayed. When
the end user specifies the instances this framework displays
actually which destination it belongs to, type and category of V PERFORMANCE EVALUATION
restaurant, accommodation and travels.
Finally the performance of top down approach
compared with bottom up approach for information retrieval
speed .The following table shown the time taken to retrieve
the results.
81 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 2, May 2010
TABLE I. PERFORMANCE COMPARISON OF TOPDOWN AND
BOTTOMUPAPPROACH FOR TRAVEL AGENCY CHOICE GRAPH II. COMPARISON GRAPH
Performance Category Top down Bottomup-
comparison approach- Enduser
Enduser choice
choice
1342ms 1319ms
Luxury
Time taken
for
Medium 1248ms 1224ms
Information
Retrieval
Low 1170ms 1143ms
Graph II represents the performance comparison for end user
choice using top down as well as bottom up approach. It
shows that time taken to retrieve the information using bottom
GRAPH I. COMPARISON GRAPH up approach is lesser than top down approach
VI CONCLUSIONS
This paper proposes the usage of ontology for travels
and tourism domain. It proposes a method to create and edit
ontology dynamically and a method to query for information
using ontology. This paper also proposes top down and bottom
up approaches to extract information from ontology. A
comparison of these two approaches is also provided in this
paper. When budget of travel is known and no details of
instances is provided bottom up approach can not be used. Top
down approach is suitable. Thus the tradeoff between top
down and bottom up approaches are not only based on the
performance but also on their applicability.
Graph I represents the performance comparison for end user
choice using top down as well as bottom up approach. It ACKNOWLEDGMENT
shows that time taken to retrieve the information using bottom Our thanks to Dr.R.Rudramoorthy,Principal,PSG
up approach is lesser than top down approach. College of Technology and Mr.K.Chidambaram, Director,
Grid and Cloud systems group, Yahoo software development,
PERFORMANCE COMPARISON OF TOP DOWN AND
TABLE II. India Private Limited for their support. This project is carried
BOTTOM UPAPPROACH FOR ENDUSER CHOICE out in Grid and Cloud lab,PSG College of Technology.
Top down -traveler choice Bottom up- traveler choice REFERENCES
[1] Brooke Abrahamsand Wei Dai. Architecture for Automated Annotation
and Ontology Based Querying of Semantic Web Resources
3.29 ms 3.19ms [2] Konstantinos Kotis, Semantic Web Search: Perspectives and Key
Technologies.Karlovassi, 83200 Samos, Greece.
82 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 8, No. 2, May 2010
[3]. Konstantinos Kotis, Dpaolo Ceravolo, Ernesto Damiani, Member, IEEE,
and Marco Viviani “Bottom-Up Extraction and Trust-Based Refinement of
Ontology Metadata” IEEE Transactions.
[4] Ling Li, Shengqun Tang, Lina Fang,Ruliang Xiao,Xinguo Deng,Youwei
Xu,Yang Xu, Visual Ontology Modeling Tool and Ontology Based Querying
of Semantic Web Resources, 31st Annual International Computer Software
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[5] P.H. Alesso, C. F. Smith. Developing Semantic Web Services. Canada:
Wellesey MA, 2004. 165-272.
[6] P.H. Alesso, C..F. Smith, Developing Semantic Web Servces, A K Peters
ltd, Wellesey MA, Canada, Date,2004, pp.165-272.
[7] Siegfried Handschuh, Steffen Staab. Authoring and annotation of web
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[8] T. Berners-Lee, J. Hendler, and O. Lassila, "The Semantic Web - A new
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[9] The Protégé project. http://protege.stanford.edu, 2002 On Knowledge and
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AUTHORS PROFILE
Dr G Sudha Sadasivam is working as a Professor in
Department of Computer Science and Engineering in PSG
College of Technology, India. Her areas of interest include
Distributed Systems, Distributed Object Technology, Grid
and Cloud Computing. She has published 5 books, 20
papers in referred journals and 32 papers in National and
International Conferences. She has coordinated two AICTE
– RPS projects in Distributed and Grid Computing areas.
She is also the coordinator for PSG-Yahoo Research on Grid
and Cloud computing.
Ms C Kavitha is working as a Senior Lecturer in Department
of Computer Science and Engineering in PSG College of
Technology, India. She is pursuing her research work in
Semantics in Large scale Distriduted systems. Her areas of
interest include Semantic Web Technology, Parallel
Processing and Data Structures. She has published 3 papers
in this area.
Ms M.Saravana Priya is a PG student doing her ME –
Software Engineering in CSE Department of PSG College of
Technology. Her area of interest is Semantic Web
Technology. She has published 2 papers in this area
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