Information Extraction with HMM Structures Learned by Stochastic Optimization

By Dayne Freitag, Andrew McCallum. AAAI/IAAI, 2000

317 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/02c8a0bc8bab9920e6615cfacf1df2ab3f2b1f68

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Citations in the corpus

Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data (2001, unknown): “But that would preclude the use of prior structural knowledge that has proven so valuable in information extraction tasks (Freitag & McCallum, 2000).”
Kernel Methods for Relation Extraction (2002, methodology): “A unique property of the kernel methods is that we do not explicitly generate features.”
A Generative Model for Semantic Role Labeling (2003, methodology): “In particular, recent work such as [5] uses Hidden Markov Models, including induction over the structure of the model, for the labeling t ask.”
Modeling Latent-Dynamic in Shallow Parsing: A Latent Conditional Model with Improved Inference (2008, methodology): “In the vision community, the LD-CRF model was recently proposed by Morency et al. (2007), and shown to outperform CRFs, SVMs, and HMMs for visual sequence labeling.”
Mining knowledge from text using information extraction (2005, methodology): “Several earlier IE systems used generative HMM models [4; 31]; however, discriminately-trained CRF models have recently been shown to have an advantage over HMM’s [54; 65].”
A Survey of Opinion Mining and Sentiment Analysis (2012, background): “, Conditional Random Fields (CRF) [33, 52], and Hidden Markov Models (HMM) [22, 34, 35], and sequential rule mining [60].”
Shallow Parsing with Conditional Random Fields (2003, methodology): “These tests suggest that MEMMs are signi(cid:2)cantly less accurate, but that there are no signi(cid:2)cant differences in accuracy among the other models.”
Opinion observer: analyzing and comparing opinions on the Web (2005, methodology): “Their focus is on using machine learning and NLP methods to extract/classify named entities and relations [5, 10, 14 , 20, 31].”
A survey on sentiment detection of reviews (2009, unknown): “…Airoldi, 2004; Bethard , Yu, Thornton, Hatzivassiloglou, & DanJurafsky, 2004; Bunescu & Mooney, 2004; Daille, 1996; Didier, 1995; Etzioni et al., 2004; Freitag & McCallum, 2000; Jacquemin & Bourigault, 2001; Luca & Mazzini, 2002; Riloff & Jones, 1999; Wilson, Wiebe, & Hwa, 2004; Zhai & Liu, 2005).”