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    <abstract>Cancer (a.k.a neoplasms in a broader sense) is one of the leading causes of death worldwide and its incidence is expected to exacerbate. To respond to the critical need from the society, there have been rigorous attempts for the cancer research community to develop treatment for cancer. Accordingly, we observe a surge in the sheer volume of research products and outcomes in relation to neoplasms. In this talk, we introduce the notion of entitymetrics to provide a new lens for understanding the impact, trend, and diffusion of knowledge associated with neoplasms research. To this end, we collected over two million records from PubMed, the most popular search engine in the medical domain. Coupled with text mining techniques including named entity recognition, sentence boundary detection, string approximate matching, entitymetrics enables us to analyze knowledge diffusion, impact, and trend at various knowledge entity units, such as bio-entity, organization, and country. At the end of the talk, the future applications and possible directions of entitymetrics will be discussed.</abstract>
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%0 Conference Proceedings
%T Analyzing Impact, Trend, and Diffusion of Knowledge associated with Neoplasms Research
%A Song, Min
%Y Drouin, Patrick
%Y Grabar, Natalia
%Y Hamon, Thierry
%Y Kageura, Kyo
%Y Takeuchi, Koichi
%S Proceedings of the 5th International Workshop on Computational Terminology (Computerm2016)
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F song-2016-analyzing
%X Cancer (a.k.a neoplasms in a broader sense) is one of the leading causes of death worldwide and its incidence is expected to exacerbate. To respond to the critical need from the society, there have been rigorous attempts for the cancer research community to develop treatment for cancer. Accordingly, we observe a surge in the sheer volume of research products and outcomes in relation to neoplasms. In this talk, we introduce the notion of entitymetrics to provide a new lens for understanding the impact, trend, and diffusion of knowledge associated with neoplasms research. To this end, we collected over two million records from PubMed, the most popular search engine in the medical domain. Coupled with text mining techniques including named entity recognition, sentence boundary detection, string approximate matching, entitymetrics enables us to analyze knowledge diffusion, impact, and trend at various knowledge entity units, such as bio-entity, organization, and country. At the end of the talk, the future applications and possible directions of entitymetrics will be discussed.
%U https://aclanthology.org/W16-4701
%P 1

Markdown (Informal)

[Analyzing Impact, Trend, and Diffusion of Knowledge associated with Neoplasms Research](https://aclanthology.org/W16-4701) (Song, CompuTerm 2016)

• Analyzing Impact, Trend, and Diffusion of Knowledge associated with Neoplasms Research (Song, CompuTerm 2016)

ACL

• Min Song. 2016. Analyzing Impact, Trend, and Diffusion of Knowledge associated with Neoplasms Research. In Proceedings of the 5th International Workshop on Computational Terminology (Computerm2016), page 1, Osaka, Japan. The COLING 2016 Organizing Committee.