Neat NLP Videos

There are two neat videos that explain natural language processing. One is the wit.ai project at
http://youtu.be/G7M74_K8iiw.
 It talks about matching entities with intents using similar words.

The second video from TED talks on mapping ideas through natural language processing:
http://www.ted.com/talks/eric_berlow_and_sean_gourley_mapping_ideas_worth_spreading.html .

Google came out with their word2vec project.  This project is a great effort to make similar words to combine using the nearest vector. While this is a great effort, it some perfection needs to occur. Instead of classifying words that are similar I'm finding the approach taken by wit.ai to be better. The Google approach does not take into account the fact that words can not be multiple dimensionality. For example we say that a portrait resembles a person, not a person resembles a painting. Wit attempts to get to the heart of what a conversation is so that, as my first paper suggests, we learn from a transaction using business processing modelling language first what a conversation is and why it occurs.

About me

I am Rob Wahl and I am the writer of the paper on natural language processing called Quick Summary available at http://arxiv.org/abs/1210.3634 . I am very interested in how a computer can solve the problem of having too much information and not enough time to digest it. Quick summary works by finding recurrent themes through a paper by using a PMML or predictive model markup language called MMML (maven meta-data markup language). I am currently contributing to several open source projects including Gensim that looks as similarities between text. I also contribute to Apache projects and to the NLTK framework. In this blog I explore ways of improving the field of NLP as I hope to write another paper.