public class XSqrA_M extends WeightingModel
XSqrA_M has a high performance, and in particular has statistically significant better MAP performance than all other supervised models on the GOV2 collection. MAP for short (title only) and medium (title+description) topics, and comparative p values (two-tailed paired t-test) compared to supervised models (with optimal MAP parameter values) are as follows:
|Queries||MAP of XSqrA_M||LGD||Dirichlet_LM||PL2||BM25||In_expB2|
References Frequentist and Bayesian approach to Information Retrieval. G. Amati. In Proceedings of the 28th European Conference on IR Research (ECIR 2006). LNCS vol 3936, pages 13--24.
|Constructor and Description|
A default constructor to make this model.
|Modifier and Type||Method and Description|
Returns the name of the model, in this case "XSqrA_M"
Uses XSqrA_M to compute a weight for a term in a document.
clone, getOverflowed, getParameter, prepare, score, setCollectionStatistics, setEntryStatistics, setKeyFrequency, setParameter, setRequest
public final String getInfo()
public final double score(double tf, double docLength)
@Deprecated public final double score(double tf, double docLength, double documentFrequency, double termFrequency, double keyFrequency)
tf- The term frequency in the document
docLength- the document's length
documentFrequency- The document frequency of the term
termFrequency- the term frequency in the collection
keyFrequency- the term frequency in the query
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