Web content mining is related but different from data mining and text mining. It is related to data mining because many data mining techniques can be applied in Web content mining. It is related to text mining because much of the web contents are texts. H
Todays feature of the week post will point you to one of the hidden features of the system. As most of you certainly know one way to acquire the meta data of a publication is to use the screen scraping facility of BibSonomy.
The main task of the GenIELex project is the development of a biochemistry specific lexicon as well as of an annotated corpus for the evaluation of the system. The need for the construction of such a lexicon is illustrated by the following figures, based
The main task of the GenIELex project is the development of a biochemistry specific lexicon as well as of an annotated corpus for the evaluation of the system. The need for the construction of such a lexicon is illustrated by the following figures, based
TeSSI® (Terminology Supported Semantic Indexing) is a state-of-the-art tool that improves upon the existing search and retrieval tools by extracting the meaning out of medical free text and placing the resulting medical ‘concepts’ in the document...
TeSSI® (Terminology Supported Semantic Indexing) is a state-of-the-art tool that improves upon the existing search and retrieval tools by extracting the meaning out of medical free text and placing the resulting medical ‘concepts’ in the document ind
Text mining and web scraping involves chunk parsing and recognition of named entities (institutions, dates, titles)...The extraction of named entities is mostly based on a strategy that combines look up in gazetteers (lists of companies, cities, etc.) wit
Text mining and web scraping involves chunk parsing and recognition of named entities (institutions, dates, titles)...The extraction of named entities is mostly based on a strategy that combines look up in gazetteers (lists of companies, cities, etc.) wit
Y. Ohsawa, N. Benson, and M. Yachida. ADL '98: Proceedings of the Advances in Digital Libraries Conference, page 12. Washington, DC, USA, IEEE Computer Society, (1998)
Y. Matsuo, and M. Ishizuka. Proceedings of the Sixteenth International Florida Artificial Intelligence Research Society Conference, page 392-396. AAAI Press, (2003)
J. Chang, J. Boyd-Graber, and D. Blei. KDD '09: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, page 169--178. New York, NY, USA, ACM, (2009)
P. Kluegl, M. Atzmueller, and F. Puppe. Proceedings of the Biennial GSCL Conference 2009, 2nd UIMA@GSCL Workshop, page 233-240. Gunter Narr Verlag, (2009)
T. Rattenbury, N. Good, and M. Naaman. SIGIR '07: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, page 103--110. New York, NY, USA, ACM Press, (2007)
X. Wan, and J. Xiao. Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008), page 969--976. Manchester, UK, Coling 2008 Organizing Committee, (August 2008)