@article{139,
  author = {Taeho Jo},
  title = {NTSO (Neural Text Self Organizer): A New Neural Network for Text Clustering},
  journal = {Journal Of Networking Technology},
  year = {2010},
  volume = {1},
  number = {1},
  doi = {},
  url = {http://www.dline.info/jnt/fulltext/v1n1/4.pdf},
  abstract = {This research proposes an alternative representation of documents and a new neural network using the proposed representation as its input and weight vectors, for more reliable text clustering. Almost traditional neural networks dictate representation of raw data into numerical vectors for their application to real tasks including text clustering. The traditional representation may lead to difficulties depend on the type of raw data. For example, in text clustering, encoding textual data given as raw data into numerical vectors leads to two main problems: huge dimensionality and sparse distribution. This research addresses the two problems at same time by proposing the alternative representation and a new neural network, called NTSO. The experiments in this research show that the proposed neural network is more practical than k-means algorithm, Kohonen Networks, and single pass algorithm, with respect to clustering performance and clustering speed.},
}