Traversal and relations discovery among business entities and people using

Semantic Web technologies and Trust Management

Dejan LavbičDejan.Lavbic@fri.uni-lj.si

http://www.lavbic.net

University of Ljubljana,Faculty of Computer and Information Science,

SLOVENIA

Agenda Motivation » semantic integration » problem of trust

Problem Trust and semantic integration of data »

modelling trust

SocioLeaks case study » technology » ontologies » example case study

Conclusions

Motivation (1)

semantic integration of various data sources that include information about business entities and people

the problem of trust as a method of dealing with uncertaintyespecially when dealing with online personal

identitygovernment registers vs. online social networks,

newspaper archives etc.

Motivation (2)

Identify person from keyword and display known properties.

Sources• Wikipedia• Freebase• …

Problem (1)

Lack of semantically integrated information about online personal identity with the purpose of:coping with corruption in crossing the frontiers

of legislation,fraud detection in banks, insurance companies

and other public institutions,pattern discovery and identification.

Problem (2)

current approaches deal with integration of information from several data sources and omit or don't fully address the aspect of trust,

main focus on personal information from social networks which are not very reliable as users for various reasons tend to give false information.

Trust and semantic integration (1)

Definition of trust

Trust is …a measurable belief that utilizes personal

experiences○ experiences of others or possibly combined

experiences, to make trustworthy decisions about an entity

○ a trustworthy decision is assumed to be a transitive process such that there is a web of trust network in which a link between two entities means that a trustworthy decision has been made and the quantitative value of that trust has been evaluated.

Trust and semantic integration (2)

Modelling trust (1)

our approach is based on RDF language (extends to RDFS, OWL etc.),

different types of trust can be defined for each entitydata source trust entity trust , which further

consist of○ schema level entity trust ○ instance level entity trust

Trustvalue

type

Data source trust

Entity trust

sub class sub class

Entityhas trust

sub property

has entity trust

sub property

author

has data source trust

has schema level entity trust

has instance level entity trust

sub property sub property

Trust and semantic integration (3)

Modelling trust (2)

trust of entity e »

entity trust »

○ schema level entity trust »

○ instance level entity trust »

degree of incorporation of users' votes »

Trust and semantic integration (4)

Modelling trust (3)

trust of entity e »

entity trust »

○ schema level entity trust »

Trust and semantic integration (5)

Modelling trust » example (4)

What degree of confidence does the information about the instance of a class Person represent?

UJP

User provided

SICRIS

AJPES

Business entity

Person

sub property

Researchertitle

name

research area

code

Company

Budget user

tax numbertitle

.sub class

Transactionmonth

amount

receive

year

name

Entity

knows

.sub class.

sub class

is employed atsub class

sub property

95%

has entity trust.

send

95%

90%

has entity trust.

95%

has entity trust.

has entity trust

.sub class

has data source trust95%

has data source trust95%

90%

has entity trust.

is related to

70%

has entity trust.

80%

.has entitytrust

has data source trust50%

95%

has entity trust.

has data source trust90%

SocioLeaks case study (1)

Technology

Open source technologies that support current W3C standards in Semantic Web and linked-data applicationsApache Jena framework

Apache Jena Store layer

in-memory

TDB

native tuple store

files

Apache Jena Inference layer

rule reasoner (RDFS++ subset)

Apache Jena Ontology layer

RDF

Ontology

SPARQL

HTML, text, RDF/XML,

relational data

Apache Jena

Fuseki

http

Java invoke

Parsers and writers

WSO2 Mashup server D2R server OpenCalais

SocioLeaks case study (2)

Ontologies

Slovenian Current Research Information System (SICRIS)

Researcher

titlename

research area

code Engagementposition

employment date

Research organisation

Research group

is part of

name

name

.in.

Bibliographic unit

.holds.

is author

Projectname

code

duration

collaborates.classification

collaborates

Program

name

code

durationclassification

collaborates

collaborates

title

year

sourcetype

Slovenian Business Register (AJPES)

Partner

Business entity

owns

street name and numberpost office code

citycountry

Address

tax number

registration number

business register entry date

legal organization form

number of parts

sub class

sub class

titleshort title

sub property

full titlesub property Role

representative number

type of representative

date of appointment

manner of representation

restrictions

represents

name

date of entrypartner number

type of responsibility for the company‘s liabilities

hascapital contribution

Equity interest

share

is registered atsub class

CompanyPublic institute

Trade unionsub class

sub class sub class

Authorized representative

name

Relations

country

Entity

Business entity

Person

sub class

sub class.

knows

type

name

Man.sub class.

Womansub class

street name and number

post office code

city

is related to

is employed atsub property

is authorized representative

sub property

is related to

sub property

is registered at the same address

sub property

has business relations

sub propertyhas family relations

sub property

has inclinationsub property

is enemy is friendsub property

sub property

is descendantsub property

is marriedsub property

is co-workersub property

is sibling.sub property.

is ancestorsub property

is parentsub property

is partnersub property

is superiorsub property

is inferiorsub property

Public Payments Administration of the Republic of Slovenia (UJP)

Budget user

tax numberidentification numbertype

street name and numberpost office code city

Address

is registered at

name

Company

tax numbername

Transactionyear

monthamount

.send.

receive

The Health Insurance Institute of Slovenia (ZZZS)

Organization unit

name

code

Branch

is part of

name

code

Gynaecologist

Employee

DentistPhysician

name

code

activity subsidy level

occupancy

employed at

sub class

sub class

sub class

Telephone Directory of Slovenia (iTIS)

Entityname

street name and numberpost office code

city

phone number

Business entity

Person

sub class sub classimports

imports

imports

imports

imports

SocioLeaks case study (3)

Prototype example (1)

Sponka d.o.o.

Ivan Novak

Janez Horvat

Ministry of Foreign Affairs

Kulinar s.p.

Marija Krajnc

Ana Horvat

sends transaction

is authorized representative

is partner

is partner

is employed at

is authorized representative

is partner

is daughterDC12

1

Neighbourhood

1 2 3 4 5 6

Trust

0% 50% 100%

Timeline

1 3 52 4

Scale: Year

Filter

Knows relation

Business relations

Family relations

EntityBusiness entityPersonOther

SiblingDescendant

MarriedAncestor

Social relations

SonDaughter

Status

Searching for connections between entity „Ana Horvat“ and entity „Ivan Novak“ while traversing neighbourhood of 3 entities and considering information with trust higher than 50%.

Voting for the relationship „Marija Krajnc is daughter of Ana Horvat“.

+1

Discover relationships

Ana Horvat (Ljubljana …) ü 1st entity

Ivan Novak (Sežana …) ü 2nd entity

:

:

92%

92%

92%

90%

90%

90%

90% 86%

86%

88%

87%

86%

74%

95%53%

Traversal is performed by specifying entry point of 1 or 2 entities.

Defining the length of property paths to follow.

Considering the time dimension.

The trust level threshold.

Filtering of entities and relations.

SocioLeaks case study (4)

Prototype example (2)

Sponka d.o.o.

Ivan Novak

Janez Horvat

Ministry of Foreign Affairs

Kulinar s.p.

Marija Krajnc

Ana Horvat

sends transaction

is authorized representative

is partner

is partner

is employed at

is authorized representative

is partner

is daughterDC12

1

Neighbourhood

1 2 3 4 5 6

Trust

0% 50% 100%

Timeline

1 3 52 4

Scale: Year

Filter

Knows relation

Business relations

Family relations

EntityBusiness entityPersonOther

SiblingDescendant

MarriedAncestor

Social relations

SonDaughter

Status

Searching for connections between entity „Ana Horvat“ and entity „Ivan Novak“ while traversing neighbourhood of 3 entities and considering information with trust higher than 50%.

Voting for the relationship „Marija Krajnc is daughter of Ana Horvat“.

+1

Discover relationships

Ana Horvat (Ljubljana …) ü 1st entity

Ivan Novak (Sežana …) ü 2nd entity

:

:

92%

92%

92%

90%

90%

90%

90% 86%

86%

88%

87%

86%

74%

95%53%

Conclusion Proposed the use of Semantic Web

technologies for semantic integration of data about business entities and people coupled with trust layer. Several layers of trust – data source, schema

level entity and instance level entity.Enables filtering the data based on the user

preference.Application of the approach is feasible in several

cases – banks, insurance companies etc.

Discussion Thank you for your attention!

Questions, comments and critiques are more than welcome!

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