TY - GEN
T1 - Comparing relevance feedback algorithms for web search
AU - Vinay, Vishwa
AU - Wood, Ken
AU - Milic-Frayling, Natasa
AU - Cox, Ingemar J.
PY - 2005
Y1 - 2005
N2 - We evaluate three different relevance feedback (RF)algorithms, Rocchio, Robertson/Sparck-Jones (RSJ)and Bayesian, in the context of Web search. We use a target-testing experimental procedure whereby a user must locate a specific document. For user relevance feedback, we consider all possible user choices of indicating zero or more relevant documents from a set of 10 displayed documents. Examination of the effects of each user choice permits us to compute an upper-bound on the performance of each RF algorithm.We ind that there is a significant variation in the upper-bound performance o the three RF algorithms and that the Bayesian algorithm approaches the best possible.
AB - We evaluate three different relevance feedback (RF)algorithms, Rocchio, Robertson/Sparck-Jones (RSJ)and Bayesian, in the context of Web search. We use a target-testing experimental procedure whereby a user must locate a specific document. For user relevance feedback, we consider all possible user choices of indicating zero or more relevant documents from a set of 10 displayed documents. Examination of the effects of each user choice permits us to compute an upper-bound on the performance of each RF algorithm.We ind that there is a significant variation in the upper-bound performance o the three RF algorithms and that the Bayesian algorithm approaches the best possible.
KW - Evaluation
KW - Relevance feedback
KW - Web search
UR - https://www.scopus.com/pages/publications/77953049528
U2 - 10.1145/1062745.1062864
DO - 10.1145/1062745.1062864
M3 - Conference contribution
AN - SCOPUS:77953049528
SN - 1595930515
SN - 9781595930514
T3 - 14th International World Wide Web Conference, WWW2005
SP - 1052
EP - 1053
BT - 14th International World Wide Web Conference, WWW2005
T2 - 14th International World Wide Web Conference, WWW2005
Y2 - 10 May 2005 through 14 May 2005
ER -