Skip to search formSkip to main contentSkip to account menu

Perplexity

Known as: Perplexity consumer, Perplexities, PP 
In information theory, perplexity is a measurement of how well a probability distribution or probability model predicts a sample. It may be used to… 
Wikipedia (opens in a new tab)

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
A language model based in continuous representations of words is pre- sented, which has been applied to a statistical machine… 
2011
2011
Popular algorithms for modeling the influence of entities in networked data, such as PageRank, work by analyzing the hyperlink… 
2004
2004
Content-based image retrieval (CBIR) addresses the problem of finding images relevant to the users' information needs, based… 
2004
2004
This paper presents modifications to a standard probabilistic context-free grammar that enable a predictive parser to avoid… 
2000
2000
In the standard approach to speech recognition, the goal is to find the sentence hypothesis that maximizes the posterior… 
2000
2000
Transformation-based learning has been successfully employed to solve many natural language processing problems. It has many… 
2000
2000
This paper describes the use of a weighted mixture of class-based n-gram language models to perform topic adaptation. By using a… 
1998
1998
Phrase(cid:0)based language models have been recognized to have an advantage over word(cid:0)based language models since they…