@InProceedings{song:2016:Computerm2016,
  author    = {Song, Min},
  title     = {Analyzing Impact, Trend, and Diffusion of Knowledge associated with Neoplasms Research},
  booktitle = {Proceedings of the 5th International Workshop on Computational Terminology (Computerm2016)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {1},
  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.},
  url       = {http://aclweb.org/anthology/W16-4701}
}