Learning a Probabilistic Model of Event Sequences from Internet Weblog Stories

By Mehdi Manshadi, Reid Swanson, Andrew S. Gordon. 2008

56 citations recorded by the source corpus.

Subfields: Probabilistic & Bayesian Methods

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In Probabilistic & Bayesian Methods

Citations in the corpus

A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories (2016, background): “Personal stories from daily weblogs are good sources of commonsense causal information (Gordon and Swan-a son, 2009; Manshadi et al., 2008), but teasing out useful information from noisy blog entries is a problem of its own.”
Skip N-grams and Ranking Functions for Predicting Script Events (2012, methodology): “…sub-task: given an event or partial chain of events, predict other events that belong to the same script (Chambers and Jurafsky, 2008; Chambers and Jurafsky, 2009; Chambers and Ju-rafsky, 2011; Manshadi et al., 2008; McIntyre and Lapata, 2009; McIntyre and Lapata, 2010; Regneri et al., 2010).”
Statistical Script Learning with Multi-Argument Events (2014, methodology): “There is a small body of recent research on automatically learning probabilistic models of scripts from large corpora of raw text (Manshadi et al., 2008; Chambers and Jurafsky, 2008; Chambers and Jurafsky, 2009; Jans et al., 2012).”
Learning Script Knowledge with Web Experiments (2010, background): “proaches to automatically learning event chains from corpora (Chambers and Jurafsky, 2008b; Chambers and Jurafsky, 2009; Manshadi et al., 2008).”
Say Anything: A Massively Collaborative Open Domain Story Writing Companion (2008, background): “This is not an easy problem to solve but solutions may include event prediction and modeling [16][17][18] and integrating coreference”
Script Induction as Language Modeling (2015, methodology): “(Chambers, 2013; Cheung et al., 2013; Cheung and Penn, 2013; Frermann et al., 2014; Manshadi et al., 2008; Modi and Titov, 2014; Regneri et al., 2010) inantly as a method for evaluating script knowledge, is more productively thought of simply as a language modeling task.”