Microsoft Cambridge at TREC-9: Filtering Track

Microsoft Cambridge at TREC-10: Filtering and Web Tracks

This report is concerned with the Adaptive Filtering and Web tracks. There are separate reports in this volume [1, 2] on the Microsoft Research Redmond participation in QA track and the Microsoft Research Beijing participation in the Web track.. Two runs were submitted for the Adaptive Filtering track, on the adaptive ltering task only (two optimisation measures), and several runs for the Web t...

Microsoft Cambridge at TREC 2002: Filtering Track

Six runs were submitted for the Adaptive Filtering track, four on the adaptive filtering task (ok11af??), and two on the routing task (msPUM?). The adaptive filtering system has been somewhat modified from the one used for TREC–10, largely for efficiency and flexibility reasons; the basic filtering algorithms remain similar to those used in recent TRECs. For the routing task, a completely new s...

Microsoft Cambridge at TREC 13: Web and Hard Tracks

All our submissions from the Microsoft Research Cambridge (MSRC) team this year continue to explore issues in IR from a perspective very close to that of the original Okapi team, working first at City University of London, and then at MSRC. A summary of the contributions by the team, from TRECs 1 to 7 is presented in [3]. In this work, weighting schemes for ad-hoc retrieval were developed, insp...

The TREC–9 Filtering Track Final Report

The TREC–9 filtering track measures the ability of systems to build persistent user profiles which successfully separate relevant and non-relevant documents. It consists of three major subtasks: adaptive filtering, batch filtering, and routing. In adaptive filtering, the system begins with only a topic statement and a small number of positive examples, and must learn a better profile from on-li...

Logical Analysis of Data in the TREC-9 Filtering Track