At the last Search Engines Architecture lecture we discussed LSI and Terrier. Great questions were raised. Some of these follows:

Q: How many dimensions to keep?
A: This is done by trial and error. I have a research project on the topic. None of the current ways of addressing this problem convince me.

Q: How do we compute a truncated version of the initial matrix, A?
A: After SVDing A, truncate U, S, and V by retaining the first k columns of U and V (rows of V transpose) and the first k diagonal elements of S. Multiply these as discussed in class to get A truncated.

Q: To compute the query vector in the reduced space, do we need to compute A truncated for each query?
A: No. The new coordinates of this vectors are defined as
q = qTUkSk-1
This means that A can be called from the cache. See the fast track tutorial
over at Mi site.

Q: Do I need to compute A truncated each time a new document is added or previous are modified?
A: For small matrices the answer is YES. However, for huge matrices we can resource to updating/appending techniques. Some of these add doc vectors without recomputing the previous matrix. There is a point wherein this can compromise orthogonality, though.

Q: How do I use Desktop Terrier?
A: Follow the instructions provided in the updated version of Lab Report 2.