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Improvement of Chance Index in Consideration of Cluster Information

  • Ryosuke SagaEmail author
  • Yukihiro Takayama
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 528)

Abstract

This paper describes an improved chance index for chance discovery. A chance is an important event or circumstance that can be used by analysts to make decisions. Discovery chance, i.e., chance discovery, is important for knowledge to be used effectively in understanding the background and causes hidden in a dataset. However, chance discovery depends on analyst’s inference. Therefore, we propose a chance index that quantitatively evaluates chance. The method is based on betweenness centrality and the strength of co-occurrence. This study improves the accuracy of chance index by considering cluster information.

Keywords

Knowledge extraction Co-occurrence network Chance index Chance discovery 

Notes

Acknowledgement

This research was supported by the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan Society for the Promotion of Science (JSPS), Grant-in-Aid for Scientific Research (A) and (C), 25240049, 25420448.

References

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Graduate School of EngineeringOsaka Prefecture UniversitySakaiJapan

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