Bibliography and links updates

As I try to put my notes in order by the end of this year, I changed a series of references, most notably in the bibliography and in the links sections.

Bibliography

I just updated the bibliography, using new categories. I divided the references in two main sections:

Corpus Linguistics, Complexity and Readability Assessment

Background

Links

First of all, I updated the links section using the W3C Link Validator. It is very useful, as it points out dead links and moved pages.

Resources for German

This is a new subsection:

Other links

I added a subsection to the links about LaTeX: LaTeX for Humanities (and Linguists).

I also added new tools and new Perl links.

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Selected recent discoveries

Here are a few links about interesting things that I recently read.

Links section updates

Out:
The Noisy Channel
LingPipe

In:
doink.ch
internetactu.net

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A few links on producing posters using LaTeX

As I had to make a poster for the TALN 2011 conference to illustrate my short paper (PDF, in French), I decided to use LaTeX, even if it was not the easiest way. I am quite happy with the result (PDF).

I gathered a few links that helped me out. My impression is that there are two common models, and as I matter of fact I saw both of them at the conference. The one that I used, Beamerposter, was “made in Germany” by Philippe Dreuw, from the Informatics Department of the University of Aachen. I only had to adapt the model to fit my needs, which is done by editing the .sty file (it is self-explanatory).

The other one, BA Poster, was “made in Switzerland” by Brian Amberg, from the Computer Science Department of the University of Basel.

And here are the links :

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Resource links update

I recently updated the blogroll section and I also would like to share a few links:

As I will be teaching LaTeX soon the LaTeX links section of the blog has expanded.

Last but not least, here is an E-Book, Mining of Massive Datasets, by A. Rajaraman and J. D. Ullmann. It was made of classes taught at Stanford and is now free to use (available chapter by chapter or as a whole), very up-to-date and informative on this hot topic. It seems to be a good introduction as well. That said I cannot really review it since I am not an expert of this research field.

Here is the reference:

  • A. Rajaraman and J. D. Ullmann, Mining of Massive Datasets, Stanford, Palo Alto, CA: e-book, 2010.
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Three series of recorded lectures

Here is my selection of introductory courses given by well-known specialists in Computer Science or Natural Language Processing and recorded so that they can be followed at home.

1. Artificial Intelligence | Natural Language Processing, Christopher D. Manning, Stanford University.
More than 20 hours, 18 lectures.
Introduction to the key topics of NLP, summary of existing models.
Lecture 12 : Dan Jurafsky as a guest lecturer.
Requires the Silverlight plugin (no comment). Transcripts available.

2. Bits, Harry R. Lewis, Harvard University.
A general overview of information as quantity and quantitative methods.
Very comprehensive lecture (data theories, internet protocols, encryption, copyright issues, laws…), cut in small pieces for you to pick a focused topic.
Several formats available, links to blog posts.

3. Search Engines: Technology, Society, and Business, various lecturers, UC Berkeley.
Fall 2007, 13 lectures.
Overview of the topic.
Requires iTunes (no comment).

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