Interested in Intelligent Extraction from Graphs and High Dimensional Data? Then, watch videos or read papers from IPAM’s Graduate Summer School: Intelligent Extraction of Information from Graphs and High Dimensional Data from July 11 – 29, 2005.
Here are some great news:
1. I am getting ready for my presentation at the Intektel International Conference and Expo. I am presenting the second day of the conference on “The Impact of Search Engines in the Internet”.
2. Next week we have the ARIN Conference (American Registry of Internet Numbers) in Puerto Rico, and in June we have also in San Juan, PR the 29th ICANN Conference. WOW!
3. Taschuk Morgan has written an excellent Honour Thesis in which kindly references our tutorial on Cosine Similarity and Term Weights. Morgan writes:
As we mentioned in IR Watch – The Newsletter (got a free subscription?), although LSI (LSA) itself is not first-order co-occurrence (see Prof. Tom Landauer: Introduction to Latent Semantic Analysis), a recent thesis from Regis Newo shows that high-order co-occurrence might be at the heart of LSI and is what makes the technique works. This 2005 thesis abstract on Understanding LSI via the Truncated Term-Term Matrix states:
Here is the 2002 master thesis of Nir Oren, University of the Witwatersand, Johannnesburg:
where he proposes an interesting approach to IR using genetic algorithms. Part of his abstract states:
I am finishing reading the 2001 Master Thesis of Cameron Alexander Marlow, from MIT:
A Language-Based Approach to Categorical Analysis
where he proposed the use of Synchronic Imprints (SI) combined with LSI. Great thesis. Essentially, SI incorporates a spring model in which term frequencies are inversely proportional to their distances.