Aug 11, 2022 · This paper highlights its use surpasses established approaches, such as tf-idf, for creating rankings of documents sorted by relevance.
Aug 11, 2022 · To accomplish this, these techniques begin by estimating a probabilistic linguistic model for each article in the collection that is capable of ...
Expanding Queries with Maximum Likelihood Estimators and Language Models ... Lafferty, J., Zhai, C.: Document language models, query models, and risk minimization ...
Conference Paper Metadata: Title: "Expanding Queries with Maximum Likelihood Estimators and Language Models" Authors: Christos Karras, Aristeidis Karras, ...
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• Basic Language Models. – maximum-likelihood estimator and the zero frequency problem. – discounting, interpolation techniques. – Bayesian estimation.
Approach: View each document as a language model and compute the probability that it generates the query: – Use actual document to estimate the LM's parameters.
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We propose a Bayesian extension to the ad-hoc Language Model. Many smoothed estimators used for the multinomial query model in ad-hoc Language Models ...
In this article, we introduce a simple method of query expansion using the naïve Bayes assumption, that is in-line with the language model since it is derived ...
Mar 19, 2024 · This exercise demonstrates the effectiveness of Language Models for Information Retrieval (LMIR) in predicting document relevance to queries.