TY - GEN
T1 - Query performance prediction for entity retrieval
AU - Raviv, Hadas
AU - Kurland, Oren
AU - Carmel, David
PY - 2014
Y1 - 2014
N2 - We address the query-performance-prediction task for entity retrieval; that is, retrieval effectiveness is estimated with no relevance judgements. First we show how to adapt state-of-the-art query-performance predictors proposed for document retrieval to the entity retrieval domain. We then present a novel predictor that is based on the cluster hypothesis. Evaluation performed with the INEX entity ranking track collections shows that our predictor can often out-perform the most effective predictors we experimented with.
AB - We address the query-performance-prediction task for entity retrieval; that is, retrieval effectiveness is estimated with no relevance judgements. First we show how to adapt state-of-the-art query-performance predictors proposed for document retrieval to the entity retrieval domain. We then present a novel predictor that is based on the cluster hypothesis. Evaluation performed with the INEX entity ranking track collections shows that our predictor can often out-perform the most effective predictors we experimented with.
KW - Entity retrieval
KW - Query performance prediction
UR - http://www.scopus.com/inward/record.url?scp=84904558114&partnerID=8YFLogxK
U2 - 10.1145/2600428.2609519
DO - 10.1145/2600428.2609519
M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???
AN - SCOPUS:84904558114
SN - 9781450322591
T3 - SIGIR 2014 - Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval
SP - 1099
EP - 1102
BT - SIGIR 2014 - Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval
T2 - 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2014
Y2 - 6 July 2014 through 11 July 2014
ER -