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Context Based Ontology Inference System Using Multi-Criteria

Decision Making

JaeGil.Lee*1, YongJin.Joo2, SooHong.Park3

(mspa7da@gmail.com, Yjjoo75@uos.ac.kr, shpark@inha.ac.kr)

Abstract

LBS services are user-centric location based information services,

whose importance has been discussed as an essential engine in

an Ubiquitous Age. Recent researches have provided intelligent

services which provide relevant information on the basis of

information on users through context awareness, instead of

providing information merely. However, current researches

provide information to users through single-reference reasoning

using basic information on users and preference information, but

there is a limit that they couldn't reflect decision making according

to users' preference and their selection standards. So, this study

has constructed an ontology of basic information on users,

preference and space preference and cost value ontology of

giving weights to selection standards for decision-making, in order

to overcome such limit. Accordingly, it suggests an ontology

reasoning system that enables users to derive recommended

results suitable for them through selection standard reasoning

according to users' various preferences. In case of construction of

the ontology, it could construct personal characteristics of users,

knowledge on preference and knowledge on spatial and

geographical preference and integrate a function of reasoning

relevant information through construction of cost value ontology

1 Dept. of GeoInformatic Engineering, In-ha University, Master`s course 2 Institute of Urbarn Science, University of Seoul, Research Professor 3 Dept. of GeoInformatic Engineering, In-ha University, Associate Professor

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for various selection standards with functions of spatial data

management of GIS system, spatial query and map display. Thus,

this study showed it could support multi-criteria decision making

by giving weight according to users' preference using AHP

technique, instead of service provision through simple context

awareness of users, and provide actual and personalized

information to users.

Key words: Spatial information, intelligent geospatial service,

service classification matrix, service domain, service intelligent

level, geo-location accuracy

1. INTRODUCTION

1.1 Research Background & Objectives

The context awareness means the recognition of individual’s location, time, weather,

schedule and personal preference. Current location based services(LBS) provides

the information and services simply with the users’ context based on the users’

current location including map, weather, traffic situation. .

Picture 1) Context-aware

Semantic technology was recently adapted in the LBS area while trying to get out of

providing simple information. Semantic technology is an intellectual technology

which understands the meaning in the system by giving meanings to the information.

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In order to apply the semantic technology we need the formation of systematic

mechanism for knowledge interface and the concept of the ontology. Using ontology,

it is possible to support the decision making through the communication between

users and system, and provide intelligent and flexible services which recommend the

most suitable services to the users.

Recent researches provide users with the information through the interface of single

criteria using information of users and preference. This has a limit which can not

reflect the users’ decision making with various criteria.

In order to overcome the limit, we architected ontology according to location, basic

information, preference and space preference by interpreting and context awareness

of users. After architecting the cost value ontology to give weight on the factors of

the decision making criteria, we suggest the service measures based on location can

provide the users with the recommended suitable result through multi-criteria

decision interface.

1.2 Research Configuration

In this research, we architected ontology according to location, basic information,

preference and space preference by interpreting and context awareness of users.

After architecting the cost value ontology to give weights on the elements of the

decision making criteria, we architect a GIS interface system which shows the

suitable recommended results for the users’ current location and context through

multi-criteria decision interface.

First, we analyze the previous context aware – location based systems, and investigate

the possibility of unification with the geographic data system after studying previous

researches which are based on the theories related to ontology.

Second, in order to architect ontology, we define using the Ontology Web Language

(OWL) which is the standard of the World Wide Web Consortium (W3C).

Third, since the experimental GIS interface system has spatial question functions, we

architect the ontology for users’ context awareness, individual characteristics, space

preference and the search results come from the corresponding spatial questions. And

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then, we architect the cost value ontology which is to consider the weight of the factors for

various decision making criteria.

Fourth, we apply the GIS inference system which is embodied in the area for the

experiment. After analyzing the actual interfaced result, we seek the actual

application possibility of GIS inference system through using ontology.

We used several programs in order to perform the research. To architect the

ontology we used Protege4.1-alpha, Google Map API for spatial database and the

system was developed by Apple iOS 4.01.

This research is described like below. In chapter 2, we explain the technology and the

research related to the concept of ontology. In chapter 3, we architect the ontology

according to the users’ individual characteristics and the space preference through the

users’ context awareness, and then explain about the materialization of the GIS interface

system. In chapter 4, we show the conclusion of this research and the direction of the

researches in the future.

2. Literature Review

2.1 Previous context awareness LBS

Most of the LBS have provided information based on the database. Referring

various information and search patterns according to the users and location

information, database is designed.

After inputting the information suitable for the criteria, the information match to the

condition is provided through query. In this kind of database based search method,

there could be difficulties in search about complex questions related to users’

different context because this method designs database and saves the information

according to the forecasted criteria.

In order to provide more intelligent LBS, studies of context aware LBS which

provide LBS matches for the users’ demand and considers user’s situations are

recently introduced.

After architecting ontology with consideration for users’ location information,

schedule, information of service, service operating hours and costs, these

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researches provide users with suitable services through interface for information

matches the meaning.

However, these researches did not consider users’ preference and space

preference, and cannot support analytic decision making according to the

importance of various factors for decision making.

2.2 Semantic technology for context awareness

When modeling the real world according to the specific subject, ontology does not

only define clearly the concepts which came out after agreement from relevant

individuals and groups, but also be a logical group of terms which were expressed as

a formation that computers can understand and process (World Wide Web

Consortium, 2004).

Ontology defines the terms which are used in the domain and their relations, and it

is needed to share the knowledge information and the common semantic

understanding of its architecture. It is also used for efficient reusing of domain

knowledge. The characteristics of ontology is the plentiful expressions of relations

and causal relationship, connection and expansion of the real information and the

concept system, expansion of knowledge, providing reuse, mutual application and

connecting different information and knowledge base which is possible for logical

interface.

For ontology language, there are RDF (Resource Description Framework) and

OWL (Web Ontology Language). RDF is a standard language for the technology

exchanges of metadata which was presented by W3C. For mutual application among

various metadata, RDF provides common rules about semantics, architecture and

syntax (Study on the guidelines of web ontology development, National

Computerization Agency).

3. Research Methodology

Picture 2 is ontology constitutional factors. In this research, ontology is composed

with class, relations, Instances, axioms and cost value ontology. Class is concepts of

the domain or tasks, which are usually organized in taxonomies. Class in this

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research is composed of user profile and spatial data. Relation is a type of interaction

between concepts of the domain. Instance is to represent specific elements of class.

Axiom is model sentences that are always true. This research uses a semantic

technique and applies for context-aware.

Picture 2) Ontology Constitutional factors

3.1. Context awareness based Ontology Inference System Architecture

The architecture of the total system which was suggested in this research is

comprised of ontology design part, user interface part and space database

part. Picture 3 is system architecture.

Picture 3) System Architecture

3.2 Space Preference

It is a part about important space preference among users’ context awareness.

According to the previous research which shows that users can use the services

from corresponding POI when the walking approach distance is within 400-500 m

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and the walking hours is within maximum 6 minutes, users get the spatial database

they want within the maximum 500m.

3.3 Design User Profile

In order to use users’ context awareness, users’ basic information is inputted in the

system users use. In the user profile ontology, information about users’ age, sex,

possessing card, location, preference and preferred location is architected.

3.4 Design Relation

Through context awareness, time which is the most important variable for users’

context interpretation is an important attribute for users’ selection and the system.

It is because providing the most suitable schedule for users is the subject should be

preferentially considered when choosing the operating hours of service location or

movies from theater.

Picture 4) Time Table

As we can see in the picture 4, the user’s flexible hours is from 13 to 17 o’clock.

In case of movie 1, the starting time of the movie does not match with user’s flexible

time. In case of movie 3, it is not recommended to the user because the finishing

time of the movie does not match with user’s flexible time. However, in case of movie

2, the movie starts and finishes in the range of user’s flexible time. For this reason,

movie 2 is recommended to the users under the condition of time constraint.

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3.5 Cost Value Ontology

In order to give weights on the selection criteria which are used when deciding POI

and service, cost value ontology was architected. In this study, distance rate and

discount rate were presented as selection criteria for POI and service. In order to

calculate weight, AHP Method was used.

In this study, discount rate and distance rate were selected as criteria factor of

selection. We decided the semantic scale and figure, and then organize them in a

matrix according to the decision criteria of selection. Through the pair wise

comparison between the criteria factor of selection and POI, we compare according

to the number of cases of every criteria factor of selection and POI.

Through the sum total of weight of selection criteria about for POI, the maximum

price is used for decision making, and this maximum price is applied to ontology.

3.6 Design Axiom

As knowledge which is expressed strictly, axiom is something we have to accept

without any proof of if it is right. In logic, public interest has an essential meaning to

show the knowledge which is the premise of interface.

When constructing ontology, axiom expresses strictly the definition of vocabulary

and concept. Axiom also has a function of interface about the questions of ontology

ability which is described using vocabulary and concept that are contained in

ontology.

3.7 Ontology

A mentioned above, through the users’ profile, space, constraint design, cost value

ontology, instance and axiom, the final ontology like below was architected. Picture 5

is ontology where is constructed in the last.

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Picture 5) Ontology

4. System Application

In this chapter, we describe GIS interface system which unified the architected

ontology. Before materialization, we selected Myung-dong area which is developed

as various complex business districts because our subject region was downtown.

Picture 6 is a materialized system image. It is materialized to make it possible for

basic map view, map control, spatial query, geo-tagging and route finding.

Picture 6) GIS Interface System

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In GIS interface system, there is a condition that users have to be in 400-500m of

walking approach distance and maximum 6 minutes of walking time in order to be able to

use services from the corresponding POI according to users’ space preference.

According to this condition, users can do space search for movie theaters which are

within 500m from the centered users, and search total POI which comes from the

corresponding space search.

We architect ontology using Protégé 4.1 – alpha for searched POI information and users’

context awareness.

As suitable service operators and services are interfaced to the users from the

architected ontology, at this time it is interfaced by using constraint conditions like

users’ basic information, preference, schedule and service hours.

Picture 7) Interface Result

In the picture 7, the interface result of the multi criteria decision is interfaced

through the ontology design system which is comprised of Protégé 4.1 – alpha of the

server. As decision making criteria is distance rate and discount rate, movie theater

IDs, 100003 and 100001 are interfaced according to each criteria. According to

users’ preference and current context, the recommended movie ‘Swon Brother’ was

interfaced. These interfaced information visualized the interface result through the

system users use.

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Picture 8) Result Display

Picture 9) Route Finding

In the picture 8, the interface result is visualized through the map display and

information expression by GIS interface system. It shows the names of the

corresponding movie theaters and recommended movies, and their genre and movie

hours through the interfaced result as movie theater IDs. In the picture 9, it seeks the

routes to the recommended locations from the users’ current location.

Like the above materialization and experiment result, this system proved that it

could perform multi criteria decision making interface based on the users’ profile,

location information and space preference. The interface result could bring the

accurate result while performing location based personalized services to users.

5. Conclusion & Future direction

We suggested GIS interface system which recommends the suitable services to

users through the users’ context awareness and context interpretation.

In this research, we architected ontology which gives weight on users’ individual

characteristics, spatial geographic preference, service hours of POI and criteria

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factors of decision making. After unifying interface functions and space analysis

functions, we showed the new location based service which brings the result by

interfacing suitable POI according to the users’ context awareness.

In order to verify the recommendation suitable for the individual users’ context, it

interfaced the movie schedule, current time, schedule according to the users’ flexible

hours, constraint conditions with the alliance cards of users’, recommended movie

theaters, recommended movies and movie hours from the public interest after

assuming the scenario of watching movie in the theater.

In this research, we architected ontology through the service information of users’

basic information, individual characteristics, preference, spatial geographic

preference information and POI. cost value ontology for decision making based on

users’ multi criteria was designed.

After unifying the visualized expression functions through the interface function for

multi criteria and spatial data management of GIS and spatial questions and the map

display of interface result using architected ontology and cost value ontology, we

presented the new LBS which brings out the result by interfacing the suitable POI

and service according to the users’ current context, basic information, preference

and space preference.

In the future researches, the study of tight coupling of ontology design part and GIS

system and Interface engine is needed to be processed, and more automatic and

intelligent functions are needed to be developed for the improvement of usefulness

for the suggested model.

Acknowledgements

This research was supported by a grant (06KLSGB01) from Cutting-edge Urban

Development – Korean Land Spatialization Research Project funded by Ministry of

Land, Transport and Maritime Affairs.

This work was researched by the supporting project to educate GIS experts.

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JaeGil Lee

2010 Dept. of GeoInformatic Engineering, In-ha University

Graduation (Bachelor of engineering)

2010~Present Dept. of GeoInformatic Engineering, In-ha

University Graduate school attending (Master`s course)

[Mailing Address] 253 Yonghyundong, Namgu, Incheon,

Republic of Korea 402-751 [Tel] +82-32-867-7605

[Fax] +82-32-863-1506 [Email] mspa7da@gmail.com.

[Mobile] +82-10-2854-1370 [Research Interest] Geo-Ontology, Spatial Datamining,

Mobile GIS Service Model, Spatial Analysis.

YongJin Joo

2001 Dept. of GeoInformatic Engineering, In-ha University

Graduation (Bachelor of engineering)

2003 Dept. of GeoInformatic Engineering, In-ha University

Graduation (Master of Engineering))

2009. Dept. of GeoInformatic Engineering, In-ha University

Graduation (Ph D. GeoInformatic Engineering)

2003.1-2003.12 Software Developer, MobilCom

2004.1~2005.2 Researcher, Korea Transport Database, Korea Transport

Insititute(KOTI)

2009.11~Present Research Professor, Institute of Urban Sciences, University of

Seoul

[Mailing Address] Jeonnong-Dong, Dongdaemun-Gu, Seoul 130-743, Republic of

Korea [Tel] +82-2-2210-5253 [Fax] +82-2-2246-0186 [Email] yjjoo75@uos.ac.kr

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[Mobile] +82-10-2701-7915 [Research Interest] GIS, Spatial DBMS, Telematics,

Embedded System, Urban Growth Simulation Model.

SooHong Park

1989. Seoul National University geography graduation

(bachelo of Geography)

1991. Seoul National University geography graduation

(master of Geography)

1996. Univ. of South Carolina at Columbia Graduation (Ph D.

geography)

1996.07~1997.08 Indiana University/ Research Associate

1997.09~1997.12 Seoul National University/researcher research study

1998.01~2000.02 Seoul Development Institute, Research committee

2000~Present Dept. of GeoInformatic Engineering, In-ha University, Associate

Professor

[Mailing Address] 253 Yonghyundong, Namgu, Incheon, Republic of Korea 402-751

[Tel] +82-32-860-7605 [Fax] +82-32-863-1506 [Email] shpark@inha.ac.kr.

[Mobile] +82-10-8970-9630 [Research Interest] u-GIS service model, spatial

databases, spatial data models.