טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
M.Sc Thesis
M.Sc StudentAnna Kozorovitsky
SubjectFusing Retrieved Lists Based on Inter-Document Similarities
DepartmentDepartment of Industrial Engineering and Management
Supervisor Full Professor Kurland Oren
Full Thesis textFull thesis text - English Version


Abstract


Methods for fusing document lists that were retrieved in response to a query often  utilize the retrieval scores and/or ranks of documents in the lists. We present a novel fusion approach that is based on using, in addition, information induced from inter-document similar- ities. Specifically, our methods let similar documents from different lists provide relevance-status support to each other. We use a graph-based method to model relevance-status propagation between documents. The propagation is governed by inter-document-similarities and by retrieval scores of documents in the lists. Empirical evaluation demonstrates the effectiveness of our methods in fusing TREC runs.

The performance of our most effective methods transcends that of effective fusion methods that utilize only retrieval scores or ranks.