Language models for information retrieval

By Djoerd Hiemstra. Proceedings / International Conference on Data Engineering, 2003

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Automatic image annotation and retrieval using cross-media relevance models (2003, methodology): “Given a query word, this model can be used to rank the images using a language modeling approach [12, 11, 4, 18].”
Relevance-Based Language Models (2001, methodology): “[14], Song and Croft [21], and Hiemstra [10] choose to treat the query ✎ as a sequence of independent words, rather than a binary vector, leading to a multinomial view of model ✏ ✞ :”
Character N-Gram Tokenization for European Language Text Retrieval (2004, methodology): “Miller et al. 1999, Hiemstra 2000 ) with Jelinek-Mercer smoothing (1980).”
Understanding Plagiarism Linguistic Patterns, Textual Features, and Detection Methods (2012, background): “Some models, such as language model [128] that ranks documents by using statistical methods, and probabilistic model [129] that assigns relevance scores to terms and uses probabilistic methods for document ranking, have yet to be applied for candidate retrieval and plagiarism detection.”