In ML estimation,α m estimated from document D is determined asα Thus, ML estimated generative probability of w in the hyperspherical QLMs is formulated as where v is a normalized word embedding of v. In MAP estimation,α m estimated from document D is determined aŝ where C is document collection in which all retrieved documents are included.
mAP estimated generative probability of w in the hypersherical QLms is formulated as The hyperspherical QLms can be interpreted as an extended form of categorical QLms.