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Ask HN: Best Text Mining Resources

59 points by big_data 16y ago

I plan a deeper dive into text mining this year, and am looking for some suggestions on what resources are best. A friend suggested Text Mining by Weiss, et al http://www.springer.com/computer/database+management+%26+information+retrieval/book/978-0-387-95433-2 What would you suggest?

vark 16y ago
- Modern Information Retrieval by Baeza Yates - Data Mining Book by Jiawei Han et al - Managing Gigabytes by Witten et al - Hypertext Mining book by Chakrabarti
helwr 16y ago
Managing Gigabytes (Witten) Information Retrieval (Manning) Text Compression (Bell) Natural Language Processing (Manning) Natural Language Understanding (Allen) Speech and Language Processing (Jurafsky) The Text Mining Handbook (Sanger) Statistical Machine Translation (Koehn) Data-Intensive Text Processing with MapReduce (Lin) Algorithms on strings (Gusfield) Jewels of Stringology (Crochemore) Regular Expressions (Friedl), also: http://swtch.com/~rsc/regexp/regexp1.html http://swtch.com/~rsc/regexp/regexp1.html and automata theory (Hopcroft) Practical Text Mining with Perl (Bilisoly) Natural Language Processing with Python (Bird) Computational Linguistics (Hausser) Syntactic structures (Chomsky) also check out these links: http://measuringmeasures.blogspot.com/2010/01/learning-about-statistical-learning.html http://measuringmeasures.blogspot.com/2010/01/learning-about... http://measuringmeasures.com/blog/2010/3/12/learning-about-machine-learning-2nd-ed.html http://measuringmeasures.com/blog/2010/3/12/learning-about-m... http://www.cs.technion.ac.il/~gabr/resources/resources.html http://www.cs.technion.ac.il/~gabr/resources/resources.html
- deleted 16y ago
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kunjaan 16y ago
You could ask in the Machine Learning subreddit too : http://reddit.com/r/machinelearning http://reddit.com/r/machinelearning
mindcrime 16y ago
Tapping Into Unstructured Data: http://www.amazon.com/Tapping-into-Unstructured-Data-Intelligence/dp/0132360292 http://www.amazon.com/Tapping-into-Unstructured-Data-Intelli... Mining The Talk: http://www.amazon.com/Mining-Talk-Unlocking-Unstructured-Information/dp/0132339536/ref=sr_1_1?ie=UTF8&s=books&qid=1276405985&sr=1-1 http://www.amazon.com/Mining-Talk-Unlocking-Unstructured-Inf... Text Mining Application Programming: http://www.amazon.com/Text-Mining-Application-Programming/dp/1584504609/ref=sr_1_1?ie=UTF8&s=books&qid=1276406016&sr=1-1 http://www.amazon.com/Text-Mining-Application-Programming/dp... Introduction to Information Retrieval (available freely online): http://nlp.stanford.edu/IR-book/information-retrieval-book.html http://nlp.stanford.edu/IR-book/information-retrieval-book.h...
dejv 16y ago
If you want to learn more about learning over text I will recommend you to look at those lectures: http://videolectures.net/mlas06_pittsburgh/ http://videolectures.net/mlas06_pittsburgh/ First two lectures are great introduction to this topic and third is also related, but not necessary. If you want to dive deeper to more advanced stuff I will recommend to look to the conditional random fields, which is kind of state of art of this field right now. Great tutorial: http://www.cs.umass.edu/~mccallum/papers/crf-tutorial.pdf http://www.cs.umass.edu/~mccallum/papers/crf-tutorial.pdf Wiki entry: http://en.wikipedia.org/wiki/Conditional_random_field http://en.wikipedia.org/wiki/Conditional_random_field
big_data 16y ago
Great stuff here, sure to get me going in the right direction! Thank you all!
deleted 16y ago
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59 points by big_data 16y ago

vark 16y ago

- Modern Information Retrieval by Baeza Yates - Data Mining Book by Jiawei Han et al - Managing Gigabytes by Witten et al - Hypertext Mining book by Chakrabarti

helwr 16y ago

Managing Gigabytes (Witten) Information Retrieval (Manning) Text Compression (Bell) Natural Language Processing (Manning) Natural Language Understanding (Allen) Speech and Language Processing (Jurafsky) The Text Mining Handbook (Sanger) Statistical Machine Translation (Koehn) Data-Intensive Text Processing with MapReduce (Lin) Algorithms on strings (Gusfield) Jewels of Stringology (Crochemore) Regular Expressions (Friedl), also: http://swtch.com/~rsc/regexp/regexp1.html http://swtch.com/~rsc/regexp/regexp1.html and automata theory (Hopcroft) Practical Text Mining with Perl (Bilisoly) Natural Language Processing with Python (Bird) Computational Linguistics (Hausser) Syntactic structures (Chomsky) also check out these links: http://measuringmeasures.blogspot.com/2010/01/learning-about-statistical-learning.html http://measuringmeasures.blogspot.com/2010/01/learning-about... http://measuringmeasures.com/blog/2010/3/12/learning-about-machine-learning-2nd-ed.html http://measuringmeasures.com/blog/2010/3/12/learning-about-m... http://www.cs.technion.ac.il/~gabr/resources/resources.html http://www.cs.technion.ac.il/~gabr/resources/resources.html

deleted 16y ago
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kunjaan 16y ago

You could ask in the Machine Learning subreddit too : http://reddit.com/r/machinelearning http://reddit.com/r/machinelearning

mindcrime 16y ago

Tapping Into Unstructured Data: http://www.amazon.com/Tapping-into-Unstructured-Data-Intelligence/dp/0132360292 http://www.amazon.com/Tapping-into-Unstructured-Data-Intelli... Mining The Talk: http://www.amazon.com/Mining-Talk-Unlocking-Unstructured-Information/dp/0132339536/ref=sr_1_1?ie=UTF8&s=books&qid=1276405985&sr=1-1 http://www.amazon.com/Mining-Talk-Unlocking-Unstructured-Inf... Text Mining Application Programming: http://www.amazon.com/Text-Mining-Application-Programming/dp/1584504609/ref=sr_1_1?ie=UTF8&s=books&qid=1276406016&sr=1-1 http://www.amazon.com/Text-Mining-Application-Programming/dp... Introduction to Information Retrieval (available freely online): http://nlp.stanford.edu/IR-book/information-retrieval-book.html http://nlp.stanford.edu/IR-book/information-retrieval-book.h...

dejv 16y ago

If you want to learn more about learning over text I will recommend you to look at those lectures: http://videolectures.net/mlas06_pittsburgh/ http://videolectures.net/mlas06_pittsburgh/ First two lectures are great introduction to this topic and third is also related, but not necessary. If you want to dive deeper to more advanced stuff I will recommend to look to the conditional random fields, which is kind of state of art of this field right now. Great tutorial: http://www.cs.umass.edu/~mccallum/papers/crf-tutorial.pdf http://www.cs.umass.edu/~mccallum/papers/crf-tutorial.pdf Wiki entry: http://en.wikipedia.org/wiki/Conditional_random_field http://en.wikipedia.org/wiki/Conditional_random_field

big_data 16y ago

Great stuff here, sure to get me going in the right direction! Thank you all!

deleted 16y ago

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