1. Visual Text Mining with SWAPit Detection of semantic relationships among text documents and associated data sources Andreas Becks Fraunhofer-Institute of Applied Information Technology Sankt Augustin & Aachen, Germany Aachen St.Augustin Roma, 24 novembre 2005

2. 2 © Fraunhofer-FIT 2005 Lost in the Ocean of Text Documents? Text Mining helps to explore and analyse natural-language texts uncover relationships, recognize trends group, condense pieces of knowledge categorize text information A huge amount of organisational knowledge is stored in text documents 85 to 90 percent of all corporate data according to Merrill Lynch and Gartner studies Even when DMS and desktop search are used, a huge amount of time is necessary to find important information 80% of companies and 40% of public administrations need more than one day [Zylab survey]

3. 3 © Fraunhofer-FIT 2005 SWAPit Helps You to Navigate Through Your Text Data The tool visualises semantic relationships among text documents... X-ray view for document archives

4. 4 © Fraunhofer-FIT 2005 SWAPit Integrates Text and Data Mining... and allows to navigate, search, browse and analyse text documents and associated data and metadata text documents catalogue of text categories related structured data Similarity View Category View Tools for analysis and search Fact View categorization associations

5. 5 © Fraunhofer-FIT 2005 Application Example: Document Management New text documents Protocollazione Titolario Information about type, AOO/UO, Fascicoli, etc. Project selection Document similarity helps to create fascicoli and find misclassified documents DL-based categorization

6. 6 © Fraunhofer-FIT 2005 Application Example: Monitoring News in the Textile Sector Whats up with competitors, collaborators, markets, materials, …? news ticker news categories Get a quick overview of business- relevant text information Explore documents, understand their relevance to the company

7. 7 © Fraunhofer-FIT 2005 Esempio applicativo: Monitoraggio delle notizie nel settore tessile Cosa succede riguardo la concorrenza, collaboratori, mercati, materiale,..? sorgente delle notizie categorie di notizie Si ottiene un rapido panorama delle informazioni testuali rilevanti per il business Si esplorano documenti, si capiscono importanza e rilevanza per lazienda

8. 8 © Fraunhofer-FIT 2005 Application Example: CRM in an Insurance Company Which customer type does complain about what? Which types of problems lead to contract cancellations? customer complaints categories of complaints customer and contract databases Group customer complaints based on their content Detect relationships and patterns in customer and contract data

9. 9 © Fraunhofer-FIT 2005 Esempio applicativo: CRM in una compagnia assicurativa Che tipo di cliente fa reclami e a proposito di cosa? Quali tipi di problemi portano ad una risoluzione dei contratti? reclami dei clienti categorie di reclami database clienti e contratti Si raggruppano i reclami dei clienti in base al contenuto Si individuano le correlazioni e le caratteristiche comuni nei dati dei clienti e dei contratti

10. 10 © Fraunhofer-FIT 2005 SWAPit as a Single Point of Access operational databases text documents user-specific schema & integrated access DL-based integration Virtual Integrated Database From scattered information......to integrated information multi-schema databases, distributed & data-centred access intuitive, user-centred access DL-based categorization

11. 11 © Fraunhofer-FIT 2005 Monitoring Documents with SWAPit and DL unfiltered and unstructured text documents DL-based filter conceptually filtered, relevant text documents DL-based catalogue builder 3 news in 1 minute 1 document map per day From information overflow... intuitively structured text documents...to information overview

12. 12 © Fraunhofer-FIT 2005 Displaying XML Documents in SWAPit From complex, machine-readable documents......to a human-oriented presentation data with technically rich structural annotation customized, task-oriented view web ontology metadata (selected attributes and elements) text content from specified attributes and elements XML ontology-context of specified elements

13. 13 © Fraunhofer-FIT 2005 Conclusion: Visual and Intuitive Text Mining with SWAPit SWAPit combines views on text documents and associated data sources on a single sreen Overview instead of overflow Improves quality of text access tasks Leverages knowledge sources Flexible architecture Designed to integrate Semantic Web technology Derives additional power from integration of DL technologies Can be integrated easily into existing infrastructures or company portals Can be tailored to specific needs of different market segments Long-standing experience in research and practical applications Document Management, Business Intelligence, Customer Relationship Management,... Main sectors: Insurance, Textile, Engineering, Social Science Technology has been extended in a joint project with Maurizio Lenzerini (SEWASIE)

14. 14 © Fraunhofer-FIT 2005 Grazie dellattenzione!