An Efficient Computation of the Multiple-Bernoulli Language Model
The Multiple Bernoulli (MB) Language Model has been generally considered too computationally expensive for practical purposes and superseded by the more efficient multinomial approach. While, the model has many attractive properties, little is actually known about the retrieval effectiveness of the MB model due to its high cost of execution. In this paper, we show how an efficient implementation of this model can be achieved. The resulting method is comparable in terms of efficiency to other standard term matching algorithms (such as the vector space model, BM25 and the multinomial Language Model).
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