Title language model for information retrieval

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Pretrained Transformers for Text Ranking: BERT and Beyond (2020, methodology): “This idea of using document metadata as distant supervision signals to create synthetic datasets dates backs to early 2000s [Jin et al., 2002].”
Context-Aware Document Term Weighting for Ad-Hoc Search (2020, methodology): “Various researches have shown that these fields behave like real user queries [15, 19].”
Clickthrough-based translation models for web search: from word models to phrase models (2010, background): “This problem has also been studied in [36, 20, 24, 21].”
Semantic Matching in Search (2014, unknown): “[95], referred to as title language model.”
Retrieval models for question and answer archives (2008, background): “Jin et al. [8] force other terms to have lower translation probabilities than self translations: P ( w | w ) ≥ P ( w (cid:6) = w | w ).”
Estimation of statistical translation models based on mutual information for ad hoc information retrieval (2010, methodology): “An alternative way of estimating the translation model is based on document titles [8].”
Clickthrough-based latent semantic models for web search (2011, background): “Since recently, with the growing availability of search logs, it is possible to mine implicit relevance judgments from clickthrough data, and to generate a large amount of real query-document pairs for translation model training [14].”