Measuring the likelihood property of scoring functions in general retrieval models
Measuring the likelihood property of scoring functions in general retrieval models
复制标题
测量一般检索模型中评分函数的似然属性
DOI:
10.1002/asi.21048
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发表时间:
2009
影响因子:
--
通讯作者:
Bache R
中科院分区:
文献类型:
--
作者:
Bache R
Although retrieval systems based on probabilistic models will rank the objects (e.g., documents) being retrieved according to the probability of some matching criterion (e.g., relevance), they rarely yield an actual probability, and the scoring function is interpreted to be purely ordinal within a given retrieval task. In this brief communication, it is shown that some scoring functions possess the likelihood property, which means that the scoring function indicates the likelihood of matching when compared to other retrieval tasks, which is potentially more useful than pure ranking although it cannot be interpreted as an actual probability. This property can be detected by using two modified effectiveness measures: entire precision and entire recall.
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影响因子:
0.5
作者:
Jordan L. Boyd-Graber;Philipp Koehn
通讯作者:
Jordan L. Boyd-Graber;Philipp Koehn
DOI:
10.1007/978-0-387-35973-1_354
发表时间:
2008
期刊:
--
影响因子:
--
作者:
S. Shekhar;Hui Xiong
通讯作者:
S. Shekhar;Hui Xiong
影响因子:
8.6
作者:
N. Fuhr
通讯作者:
N. Fuhr
影响因子:
1.9
作者:
Bennell, C;Canter, DV
通讯作者:
Canter, DV