Content Accessibility and Semantic Networks Processed on Foreign Natural Language Analysis

Bernard Dousset, Anass El haddadi, Josiane Mothe


In this paper we present a methodology that makes it possible to mine a document collection from a domain without knowing the language in which the documents are written. We describe in detail a method, tools and results that can be used within a digital library context for Science Watch and Competitive Intelligence. We consider a collection associated with the aquaculture domain written in Chinese and extracted from a digital library. Based on the original coding (UNICODE) of the data and the tag marking the structure of the documents, we extract key elements (authors, phrases, etc.) from within the domain and analyse them. The results are displayed in the form of graphs and networks. We extract people networks and semantic networks before examining their evolution over a period of several years. The principles developed in this paper can be applied to any language.


Text mining, graph, Semantic network, Social network, Weak signals, Competitive Intelligence

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Peters C. 2009. What happened in CLEF 2009 – Introduction to the Working Notes. Cross Lingual Evaluation Forum.

He D., Wang J., Oard D.W. and Nossal M. 2003. User-assisted query translation for interactive CLIR. Annual international ACM SIGIR conference on Research and development in information retrieval, 461-461.

Lu C., Xu Y., and Shlomo, G. 2008. Web-based Query Translation for English-Chinese CLIR. Computational Linguistics and Chinese Language Processing (CLCLP) 13(1): 61-90.

Li H., Cao Y. and Li C. 2003. Using Bilingual Web Data to Mine and Rank Translations. IEEE INTELLIGENT SYSTEMS, July/August: 54-59.

Gaolin F., Hao Y. and Fumihito N. 2006. Chinese-English term translation mining based on semantic prediction. Proceedings of the COLING/ACL on Main conference poster sessions, 199–206.

Leydesdorff L. 1995. The Challenge of Scientometrics: The development, measurement and self-organization of scientific communications. DSWO Press. Leiden University, Leiden.

White H.D. and McCain K.W. 1998. Visualizing a discipline: an author co-citation analysis of information science. JASIS 1972-1995 49(4): 327-355.

White H.D. 2003. Pathfinder networks and author co-citation analysis: A remapping of paradigmatic information scientists. JASIST 54(5): 423-434.

Zitt M. and Bassecoulard E. 1994. Development of a method for detection and trend analysis of research fronts built by lexical or co-citation analysis. Scientometrics 30: 333-351.

Mothe J. and Dkaki T. 1998. Interactive multidimensional document visualization. International ACM SIGIR conference on research and development in information retrieval, 363-364.

Chen C. 2002. Visualization of Knowledge Structures. In Handbook of Software Engineering and Knowledge Engineering. Chang, S.K. (Ed). World Scientific Pub Co Inc., Singapore.

Geroimenko V. and Chen C. (Eds). 2002. Visualizing the Semantic Web. XML-based Internet and Information Visualization. Springer, London.

Mothe J., Chrisment C., Dkaki T., Dousset B. and Karouach S. 2006. Combining mining and visualization tools to discover the geographic structure of a domain, computers, environment and urban systems. Geographic Information Retrieval (GIR) 30(4): 460-484.

Dousset B. 2009. Extraction de l’information implicite par analyse textuelle de sites Web en UNICODE. Veille Stratégique Scientifique et Technologique (CD-ROM).

Mardia K.V., Kent J.T. and Bibby J.M. 1979. Multivariate Analysis. Academic Press, London/New York.

Loubier E. and Dousset B. 2007. Visualization and analysis of relational data by considering temporal dimension. International Conference on Enterprise Information Systems, 550-553. INSTICC Press.

Roux C. 2009. Methods to extract weak signals. International Journal of Competitive Intelligence, Strategic, Scientific and Technology Watch 2(1): 23-29.



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