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

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Presentation transcript:

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

All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD 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.

All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD Our Approach How to collect and maintain profiles 1. Automatic Profile Extraction from Related Resources. How to represent profiles 2. Graph Expression by using RDF. How to retrieve profiles 3. Combination of Structured full-text Search and Text Mining Visualization. Meeting Document ( , Paper,…) ServicesPersons PlaceContents Search Engine Group An example of Related Resources of 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)

All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD Automatic Profile Extraction WorkWare++ A Web-based groupware. Relation of information of some applications semantically in the Metadata Layer. Automatic Creation of metadata. Employee Database Office Documents Scheduler RDF Employee objects RDF Document objects RDF Meeting objects Relationship Network WorkWare++ Schedule View User View Document View Text Mining Visualizer Application Layer Metadata Layer Multiple View Layer RDF Schedule objects XML Search Engine relevance & closeness Calculator Ontology Matching Architecture of WorkWare++

All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD Graph Expression (using RDF) schedule Owner Title 2003/3/11 Date Schedule Igata SW-WG Owner Title 2003/3/11 Date Employee Meeting Document N.Igata Nobuyuki Igata Igata Document Proc Lab. Author Name Organization Study of SW Tsuda Participant Ontology Matching Title 2003/3/11 Date 2003/3/10 Date Report of RDF Title Employee object Meeting object Ontology Matching Semantic WebRDFXML Keyword Relationship by Manual Document object Schedule object Integrate the same meeting from different personal schedules schedule Owner Title 2003/3/11 Date Schedule Igata Study of SW Owner Title 2003/3/11 Date Ontology Matching Semi-automatic Connections of some objects. Large-Scale Network Structure.

All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD 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).

All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD Technical Term Map To find target technologies from topic keywords. Visualizing technical terms, organizations, and their relations, that relate to a starting topic keyword.

All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD 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 Document Lab. Name Organization Employee object Document N.Igata Author 2003/3/10 Date Report of RDF, SW Title Semantic WebRDFXML Keyword Document object

All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD Personal Connection Map To find skilled groups of the target technology Visualizing human- network with the closeness of people.

All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD Employee Hiroshi Tsuda Document Lab. Name 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 2003/3/10 Date Report of RDF, SW Title Semantic WebRDF XML Keyword Document object Employee Nobuyuki Igata Document Lab. Name 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.

All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD Personal Skill Map To find the most skilled person in the group. Visualizing personal skill keywords in the time series.

All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD Document N.Igata Author 2003/3/10 Date TREC Title Semantic WebRDFXML Keyword How to make Personal Skill Map Employee Nobuyuki Igata Document Lab. Name Organization Employee object Document object 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 2003/3/10 Date Report of RDF, SW Title Semantic WebRDFXML Keyword

All Rights Reserved, Copyright © FUJITSU LABORATORIES LTD 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.