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Information Retrieval Models: Foundations and Relationships - Synthesis Lectures on Information Concepts, Retrieval, and Services (Paperback)Thomas Roelleke (author)
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Regarding intuition and simplicity, though LM is clear from a probabilistic point of view, several people stated: ""It is easy to understand TF-IDF and BM25. For LM, however, we understand the math, but we do not fully understand why it works.""
This book takes a horizontal approach gathering the foundations of TF-IDF, PRF, BIR, Poisson, BM25, LM, probabilistic inference networks (PIN's), and divergence-based models. The aim is to create a consolidated and balanced view on the main models.
A particular focus of this book is on the ""relationships between models."" This includes an overview over the main frameworks (PRF, logical IR, VSM, generalized VSM) and a pairing of TF-IDF with other models. It becomes evident that TF-IDF and LM measure the same, namely the dependence (overlap) between document and query. The Poisson probability helps to establish probabilistic, non-heuristic roots for TF-IDF, and the Poisson parameter, average term frequency, is a binding link between several retrieval models and model parameters.
Publisher: Morgan & Claypool Publishers
Number of pages: 163
Weight: 330 g
Dimensions: 235 x 191 x 9 mm
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