The new economy and the globalization trends have brought new needs for increasing international business communication and cooperation. However, it is often difficult to discover relevant information across languages and cultures in conventional information management system. In this study, we have proposed a multilingual semantic communication for automated information management through a user-friendly localized system. The theoretical model is made of a multilingual ontology based on linguistic knowledge from Wikipedia in order to provide a powerful search engine and suggestion system. Our current solution includes English, French and Chinese.

1. Softcust :
A Friendly Localized Platform for
Multilingual Semantic Communication
Fabian Cretton, Zhan Liu and Anne Le Calvé
Institute of Business Information Systems
University of Applied Sciences Western Switzerland
Sierre, Switzerland
fabian.cretton@hevs.ch, zhan.liu@hevs.ch
anne.lecalve@hevs.ch
04.2013

2. HES-SO Valais – Sierre -
Suisse

3. OVERVIEW
• Motivation
• Objectives of our solution
• Design & development
• Demonstration
• Practical implication
• Conclusion

4. MOTIVATION
Ming
Alice
Bonjour
你好
Gang
Automatic matching,
not just translation

5. Needs
• Platform to help users match their competencies, needs, offers and activities
– Natural Language Processing
– Mother tong
– Cross Language
• Technical needs
– Automatic matching platform
– Full text search
– Language's lexical semantic (synonym, hyponym, …)
– At least 3 languages : French, English, Chinese
– Computer sciences domain
– Easily extensible

6. RESEARCH QUESTION
How can semantic web technologies improve the performance
of an exchange platform in designing a friendly localized
system with multilingual semantic communication?

7. 3. Hybrid search :
semantic and
classical (for
words not in
ontology)
OBJECTIVES OF OUR SOLUTION
2 tools for
text analysis and search
Stored in RDBMS
1. Users enter their informations
in differents languages
2. Sent to semantic
engine for indexing
Both semantic and
classical solution

8. DESIGN & DEVELOPMENT
Classical Text Search Engine
• Text Search Engine - Apache Lucene: open source, high-performance, full-featured text
search-engine library

9. DESIGN & DEVELOPMENT
Multilingual database
• Wikipedia Database: multilingual, web-based,
freely available knowledge
– Java-based Wikipedia Library (JWPL)
– Extracting lexical semantic knowledge
from Wikipedia
– 21 Millions articles, 280 languages
– Three different types of information :
• Synonyms,
• Hyponyms ("type-of"),
• Meronyms ("part-of")

10. DESIGN & DEVELOPMENT
Multilingual Semantic Search Engine
WikiOnto : SKOS ontology
each term : 3 languages + a link to Synonyms,
Hyponymy and Meronmy.

11. DEMONSTRATION
Page: Me
User enter their profile in mother tong

12. DEMONSTRATION
Page: My Domain
User describe their domain of activities
and upload documents to add more
information on their products

13. DEMONSTRATION
Page: My Wish List
Criteria's search for partners :
keywords, roles, domain types, countrie and
languages.
Results given in the mother tongue of the user
The semantic matching allows cross languages
searches.

14. PRACTICAL IMPLICATION

15. CONCLUSION
• Multilingual semantic communication for automated information management through a
friendly localized platform for international communications and business models
• New ontologies, which support the exchange multilingual semantically enriched messages.
• Hybrid search : semantic and classical
• Advantages:
• Add More languages (Deutsh, Italian,…)
• Connect to Linked Open Data (wordnet, Geonames, …)
• Applied to other domains (eGov, BPMN,…)
• Thematic graph of texts

16. Merci de votre attention