All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD. 20031 An approach to KNOW-WHO using RDF Nobuyuki Igata, Hiroshi Tsuda, Isamu Watanabe and Kunio

All Rights Reserved, Copyright © FUJITSU LABORATORIES

LTD. 2003 1

An approach to KNOW-WHO using RDF

Nobuyuki Igata, Hiroshi Tsuda,Isamu Watanabe and Kunio

MatsuiFujitsu Laboratories Ltd.


LTD. 2003 2

What is KNOW-WHO Function of Knowledge Management.

Ex) Looking for experts with the specific skill.

How to collect, represent and maintain personal knowledge (so-called “Profile”)?

Previous Approaches Manual Profile Registration.

High maintenance costs. Attribute-Value pairs.

Too simple to represent complex personal knowledge.


LTD. 2003 3

Our Approach How to collect and maintain profiles

1. Automatic Profile Extraction from Related Resources.

How to represent profiles2. Graph Expression by using RDF.

How to retrieve profiles3. Combination of Structured full-text Search and

Text Mining Visualization.

MeetingDocument(E-mail, Paper,…)

Services Persons

PlaceContents

SearchEngine

Group

An example ofRelated Resourcesof humans routine work

What information does he output?(= personal skill)

What information does he input?

(= personal interest)

With whom does he work?

(= personal connection network)


LTD. 2003 4

Automatic Profile Extraction

WorkWare++ A Web-based groupwar

e. Relation of information

of some applications semantically in the Metadata Layer.

Automatic Creation of metadata.

EmployeeDatabase Office

DocumentsE-Mail Scheduler

RDF

Employeeobjects RDF

Documentobjects

RDF

Meetingobjects

RelationshipNetwork

WorkWare++WorkWare++

ScheduleView

User View

DocumentView

Text MiningVisualizer

ApplicationLayer

MetadataLayer

Multiple View Layer

RDF

Scheduleobjects

XMLSearch Engine

relevance & closenessCalculator

OntologyMatching

Architecture of WorkWare++


LTD. 2003 5

Graph Expression (using RDF)

scheduleOwner Title

2003/3/11

DateScheduleIgata

SW-WG

Owner Title

2003/3/11

Date

Employee Meeting

Document

N.Igata

Nobuyuki Igata

Igata

[email protected]

Document Proc Lab.

Author

NameE-mail

Organization

Study of SW

Tsuda Participant

OntologyMatching

Title

2003/3/11

Date

2003/3/10Date Report of

RDFTitle

Employee object Meeting object

OntologyMatching

Semantic Web RDF XML

Keyword

Relationshipby Manual

Document objectSchedule object

Integratethe same meetingfrom different personal schedules

scheduleOwner Title

2003/3/11

DateScheduleIgata

Study of SW

Owner Title

2003/3/11

Date

OntologyMatching

Semi-automatic Connections of some objects. Large-Scale Network Structure.


LTD. 2003 6

Search and Visualization

Implementation: a combination of the Structured Full-text Search Engine and the Text Mining Visualizer of the RDF data.

Know-Who searching procedure in WorkWare++ with the following steps.

M1. Find target technologies from topic keywords. (Technical Term Map).

M2. Find skilled groups of the target technology. (Personal Connection Map).

M3. Find the most skilled people in the group. (Personal Skill Map).


LTD. 2003 7

Technical Term Map

To find target technologies from topic keywords.

Visualizing technical terms, organizations, and their relations, that relate to a starting topic keyword.


LTD. 2003 8

How to make Technical Term Map

1. Search Document objects with a topic keyword.

2. Select Employee objects with the connection link from Document’s Author to Employee’s Name.

3. Get an organization name from Employee.

4. Calculate relevance of each terms by co-occurrence in Document.

Employee

Nobuyuki Igata

[email protected]

Document Lab.

NameE-mail

Organization

Employee object

Document

N.Igata Author


RDF, SWTitle


Keyword

Document object

①

②

③

④


LTD. 2003 9

Personal Connection Map

To find skilled groups of the target technology

Visualizing human-network with the closeness of people.


LTD. 2003 10

EmployeeHiroshi Tsuda

[email protected]

Document Lab.Name

E-mail

Organization

Employee object

How to make Personal Connection Map

Meeting

Igata

Study of SW

Tsuda

Participant

Title

2003/3/11

Date

Meeting object

Document

N.Igata Author


RDF, SWTitle


Keyword

Document object

EmployeeNobuyuki Igata

[email protected]

Document Lab.Name

E-mail

Organization

1. Search Document objects with keywords.

2. Select Meeting objects with the connection link from Document to Meeting.

3. Calculate Closeness of people by the co-participant relations of Meeting objects.

①

②

③


LTD. 2003 11

Personal Skill Map

To find the most skilled person in the group.

Visualizing personal skill keywords in the time series.


LTD. 2003 12

Document

N.Igata Author

2003/3/10Date TREC

Title


Keyword③④

How to make Personal Skill Map

Employee

Nobuyuki Igata

[email protected]

Document Lab.

NameE-mail

Organization

Employee object

Document object

①

②

1. Select the Employee object of a specific person.

2. Select Document objects with the connection link from Employee’s Name to Document’s Author.

3. Calculate relevance of each keywords by co-occurrence in Document objects.

4. Arrange keywords in order of the time series.

Document

N.Igata Author


RDF, SWTitle


Keyword③④


LTD. 2003 13

Conclusion

Advantages: 1. Automatic Profile Extraction

Reduce maintenance costs. 2. Graph Expression (using RDF)

Connect metadata of some applications. Represent complex information.

3. Search and Visualization Handling and Understanding of a huge RDF

network.

Future Works: Application to Fujitsu intranet and

Evaluation.