How to write a good research paper and give a good research talk

Good reference for research paper and presentation advice.

Interesting Blog for Graduate Students

I found a few posts that were useful here.

IEEE International Conference on Semantic Computing 2013

The IEEE ICSC.

NLP Resources

I am spending time this semester learning NLP since my work overlaps with NLP. I found a free ebook for learning NLP in Python. Another link for this book is here.
At the UMBC NLP course web site there are also slides available.
In particular, I have been working with OpenNLP which so far has been very useful. However, I am at the point of doing in-doc coref and having a lot of problems. There is not really any documentation on the in-doc coref api calls but I did find someone who dug into the code a bit and found a way to do it. However, so far, when executing my implementation, it runs forever. I hope to have an update soon.

Never Ending Learning (NELL)

Attended a very interesting talk related to Nell. The work is from Carnegie Mellon. If you are interested in machine learning, particularly how to perform learning over time, you may find this work of interest.

UMBC ebiquity group

Our group is performing interesting research by blending semantic computing with security, mobile devices, medical informatics and big data problems. Some of this research overlaps quite a bit with natural language processing. Read our publications to see the latest research coming from our lab.

Powerpoint Alternatives

I have been looking for an alternative to powerpoint that works reasonably well. So far OpenOffice and LibreOffice are not sufficient, especially when working on a team of Windows users. The following article provides a good list. I don't have a suggestion yet but would love to hear what others are using....

MASC 2013 Call For Papers Still Open

The 2013 Mid-Atlantic Student Colloquium on Speech, Language and Learning is still open.

System76 Ubuntu laptops

I spent over 6 months researching laptops and finally decided to go with a System76 Ubuntu laptop. It has been just less than 1 month but I am loving my new lemur. Review to come... System76 Lemur Ultra

Bias and Variance Tradeoff

There is a great blog entry that describes this from a practical standpoint. If references the following lecture also.

How to store billions of triples...for free

So far I like, http://sourceforge.net/apps/mediawiki/bigdata/index.php?title=GettingStarted need this too: http://www.openrdf.org/doc/sesame2/users/ch07.html

LDA - Step by Step in R

Was able to get an example running very quickly with this tutorial. http://www.rtexttools.com/1/post/2011/08/getting-started-with-latent-dirichlet-allocation-using-rtexttools-topicmodels.html

Topic Modeling - Great Resource

Excellent resource! http://www.cs.princeton.edu/~blei/topicmodeling.html

SVMs - Good Description

http://nlp.stanford.edu/IR-book/html/htmledition/support-vector-machines-the-linearly-separable-case-1.html

Building Templates for Basic Entity Types

http://schema.org/Person http://schema.org/Organization http://nlp.cs.nyu.edu/ene/version7_1_0Beng.html

Learning Programming by means of Python

This is a very basic beginners tutorial. Good for those just learning programming. http://cscircles.cemc.uwaterloo.ca/

Excellent List of Machine Learning Resources

A List of Data Science and Machine Learning Resources

PCA, SVD, LSA

Great links to learn and understand these concepts:
PCA Tutorial
SVD and PCA discussion
LSA Tutorial

Mining Twitter Article (Not technical)

This is an interesting article http://isc.sans.edu/diary.html?storyid=5728 due to the fact that they have links that are interesting related to mining Twitter. It is a little outdated and a few of the links do not work but still semi-useful. Keep in mind data sets that were previously available, for example http://snap.stanford.edu/data/twitter7.html, are no longer available due to a Twitter request (read about it here). However you can still use the Twitter API to get data, you are just limited to the number of tweets you can get per day/session (can't remember). Also useful is this article.

Paper Summary - Short text classification in twitter to improve information filtering

Short text classification in twitter to improve information filtering, B. Sriram and D. Fuhry and E. Demir and H. Ferhatosmanoglu,2010
This paper describes research that classifies tweets using a reduced set of features. In this approach they try to classify text into the following set of classes "News, Events, Opinions, Deals, and Private Messages". The problem they present is the curse of dimensionality problem that results from trying to conquer the spareness issue related to classifying twitter messages. Other research typically uses external knowledge bases to support tweet classification. They argue this can be slow due to the need to excessively query the external knowledge base. Important points about this paper:
1. They provide a very useful discussion of Twitter and tweets
2. How they classify tweets is interesting worth another review