Near real time information mining in multilingual news

ABSTRACT

This paper presents a near real-time multilingual news monitoring and analysis system that forms the backbone of our research work. The system integrates technologies to address the problems related to information extraction and analysis of open source intelligence on the World Wide Web. By chaining together different techniques in text mining, automated machine learning and statistical analysis, we can automatically determine who, where and, to a certain extent, what is being reported in news articles.

REFERENCES

• 1: Best, C. van der Goot, E. Blackler, K. Garcia, T. and Horby, D. Europe Media Monitor. Technical Report EUR 22173 EN, European Commission, 2005.
• 2: {Steinberger, R. and Pouliquen, B. Cross-lingual Named Entity Recognition. Journal Linguisticae Investigationes, Special Issue on Named Entity Recognition and Categorisation, LI 30:1 (2007) John Benjamins Publishing Company. ISSN 0378-4169. (2007) 135--162.
• 3: Piskorski, J. Tanev, H. Atkinson, M. and van der Goot, E . Cluster-Centric Approach to News Event Extraction. Proceedings of the International Conference on Multimedia & Network Information Systems (Wroclaw, Poland September 2008). IOS Press.
• 4: Piskorski, J. CORLEONE -- Core Linguistic Entity Online Extraction. Technical Report EUR 23393 EN, European Commission, 2008.
• 5: Pouliquen, B, Tanev, H. and Atkinson, M. (2008). Extracting and Learning Social Networks out of Multilingual News. Proceedings of the Social Networks and Application tools workshop (Skalica, Slovakia, Septembe

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Linguistic processing

General Terms:
Algorithms, Experimentation

Keywords:
automated media monitoring, information mining and analysis, multi-linguality, open source text