Difference between revisions of "BA/app"
| Line 19: | Line 19: | ||
=== Error Detection === | === Error Detection === | ||
| − | [http://www.aclweb.org/anthology/O13-1022 error detection using local word bigram and trigram] | + | [http://www.aclweb.org/anthology/O13-1022 error detection using local word bigram and trigram] + some others |
=== Somewhat similar problems being solved === | === Somewhat similar problems being solved === | ||
| + | [http://www.anthology.aclweb.org/P/P14/P14-2072.pdf Cross-cultural Deception Detection]. It uses unigrams + LIWC (which is more psychological and less relevant) | ||
| + | |||
[http://aclweb.org/anthology/D/D15/D15-1133.pdf Deception detection] -- has examples of extracted features which I might use | [http://aclweb.org/anthology/D/D15/D15-1133.pdf Deception detection] -- has examples of extracted features which I might use | ||
[http://web.eecs.umich.edu/~mihalcea/papers/mihalcea.acl09.pdf] -- lie detector | [http://web.eecs.umich.edu/~mihalcea/papers/mihalcea.acl09.pdf] -- lie detector | ||
| + | [http://delivery.acm.org/10.1145/2390000/2388617/p1-hauch.pdf?ip=149.205.109.95&id=2388617&acc=OPEN&key=4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E6D218144511F3437&CFID=1008304166&CFTOKEN=69973089&__acm__=1511275273_f72fd72f6e2433e82566681fc1a564cb Linguistic Cues to Deception Assessed by Computer Programs: A Meta-Analysis] -- also ideas of possible features that might be interesting to look into. | ||
| + | |||
== Random == | == Random == | ||
[https://www.safaribooksonline.com/library/view/natural-language-annotation/9781449332693/ Natural Language Annotation for Machine Learning] ebook, seems to cover quite a lot | [https://www.safaribooksonline.com/library/view/natural-language-annotation/9781449332693/ Natural Language Annotation for Machine Learning] ebook, seems to cover quite a lot | ||
| + | [http://lit.eecs.umich.edu/downloads.html#Cross-Cultural%20Deception downloads and demos -- incl datasets for CL lying detection -- generally interesting | ||
Revision as of 13:58, 26 November 2017
Contents
Primary sources
Computer linguistics: CL intro
Genetic Algorithms: An introduction to genetic algorithms
Resources
Text classification
Natural language classification with Python:Book, especially learning to classify text
With machine learning: with tensorflow and generally nns: [1] Machine Learning, NLP: Text Classification using scikit-learn, python and NLTK Working with scikit and text data
Error Detection
error detection using local word bigram and trigram + some others
Somewhat similar problems being solved
Cross-cultural Deception Detection. It uses unigrams + LIWC (which is more psychological and less relevant)
Deception detection -- has examples of extracted features which I might use [2] -- lie detector Linguistic Cues to Deception Assessed by Computer Programs: A Meta-Analysis -- also ideas of possible features that might be interesting to look into.
Random
Natural Language Annotation for Machine Learning ebook, seems to cover quite a lot [http://lit.eecs.umich.edu/downloads.html#Cross-Cultural%20Deception downloads and demos -- incl datasets for CL lying detection -- generally interesting
