This is the project page for SecondString, an open-source Java-based package of approximate string-matching techniques. This code was developed by researchers at Carnegie Mellon University from the Center for Automated Learning and Discovery, the Department of Statistics, and the Center for Computer and Communications Security.
SecondString is intended primarily for researchers in information integration and other scientists. It does or will include a range of string-matching methods from a variety of communities, including statistics, artificial intelligence, information retrieval, and databases. It also includes tools for systematically evaluating performance on test data. It is not designed for use on very large data sets.
Markdown is a text-to-HTML conversion tool for web writers. Markdown allows you to write using an easy-to-read, easy-to-write plain text format, then convert it to structurally valid XHTML (or HTML).
The nonsense which follows is a Markov Chain based upon patterns in some pieces of English text. Word-Unit Nonsense uses patterns about words that tend to follow one another. Character-Unit Nonsense uses letters.
Beautiful visualizations of how language differs among document types. - GitHub - JasonKessler/scattertext: Beautiful visualizations of how language differs among document types.
DadaDodo is a program that analyses texts for word probabilities, and then generates random sentences based on that. Sometimes these sentences are nonsense; but sometimes they cut right through to the heart of the matter, and reveal hidden meanings.
markdown-mode is a major mode for editing Markdown-formatted
text files in GNU Emacs. markdown-mode is free software, licensed
under the GNU GPL.
F. Arnold, und R. Jäschke. Proceedings of the Workshop on Natural Language Processing for Digital Humanities at ICON 2021, Seite 55--63. NLP Association of India, (2021)
C. Au Yeung, und A. Jatowt. Proceedings of the 20th ACM International Conference on Information and Knowledge Management, Seite 1231--1240. New York, NY, USA, ACM, (2011)
E. Breck, Y. Choi, und C. Cardie. IJCAI'07: Proceedings of the 20th International Joint Conference on Artifical Intelligence, Seite 2683--2688. San Francisco, CA, USA, Morgan Kaufmann Publishers Inc., (2007)
S. Dori-Hacohen, und J. Allan. Proceedings of the 22nd ACM international conference on Conference on information &\#38; knowledge management, Seite 1845--1848. New York, NY, USA, ACM, (2013)
M. Hearst. Proceedings of the 14th conference on Computational linguistics, 2, Seite 539--545. Stroudsburg, PA, USA, Association for Computational Linguistics, (1992)
C. Henning, und R. Ewerth. Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval, Seite 14--22. New York, NY, USA, ACM, (2017)
A. Hotho, S. Staab, und G. Stumme. Knowledge Discovery in Databases: PKDD 2003, 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, Volume 2838 von LNAI, Seite 217-228. Heidelberg, Springer, (2003)
A. Hotho, S. Staab, und G. Stumme. Proceedings of the 2003 IEEE International Conference on Data Mining, Seite 541-544 (Poster. Melbourne, Florida, IEEE Computer Society, (November 2003)
S. Jänicke, T. Efer, M. Büchler, und G. Scheuermann. Computer Vision, Imaging and Computer Graphics - Theory and Applications, Seite 153--171. Cham, Springer International Publishing, (2015)