So, that's that.... ECIR paper submitted.... The results according to me are good and did get some encouraging remarks from Gareth as well... Have to keep my fingers crossed... Nowadays the focus of IR research is shifting from the more traditional paradigm to the web-based personalized retrieval using tons of query logs and user session information.
The paper submitted to the ECIR sticks to the traditional paradigm and hence I'm apprehensive of its acceptance. The terms "multi-lingual", "multi-session", "personalization", "click-through data" are particularly eye-catching to the reviewers and my paper doesn't contain any of these terms.. :(
A lot depends on the acceptance of this paper as far as framing of my PhD. proposal is concerned...
All this while after submitting the ECIR paper, I implemented LM in Lucene for the INEX feedback track but sadly it didn't work and I didn't have the time to debug it. So I had to stick to the default tf-idf model of Lucene for the task. This track gave me a chance to test sentence based expansion method on true relevance judgments. Instead of working with real sentence boundaries I worked with pseudo-sentences (word windows of fixed lengths) and added terms from the most similar windows to the query.
It worked well on the training topics. MAP jumped from .43 (using baseline Rocchio feddback) to .49 (using my method). I submitted three implementations to the track, one using a fixed number of terms and the other two using a variable number of terms directly and inversely proportional to the length of the relevant segments.
During all this busy schedule of mine I also had to help Wei out in her recommender system work. I got involved in the work too, suggested her to use the INEX collection and generated some retrieval results which she could use.