TY  - BOOK
AU  - Farida Mohamed Sabry
AU  - Mayada Hadhoud , 
AU  - Nevin Darwish , 
TI  - Learning to rank for spoken content transcriptions / 
PY  - 2018///
CY  - Cairo : 
PB  - Farida Mohamed Sabry , 
KW  - Learning to rank
KW  - Spoken content retrieval
KW  - Spoken transcriptions
N1  - Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Computer Engineering; Issued also as CD
N2  - This thesis addresses the problem of ranking of spoken content retrieval (SCR). It shows the effectiveness of applying learning to rank techniques for the ranking of transcriptions based on features extracted from the metadata and the timed spoken content transcription with respect to one of the base- line unsupervised traditional scoring. Algorithms for reduction and bagging of features are implemented that outperform the state-of-art algorithms
UR  - http://172.23.153.220/th.pdf
ER  -