2009 GeneralizedExpectCritforBootstrap...

• (Bellare & McCallum, 2009) ⇒ Kedar Bellare, and Andrew McCallum. (2009). “Generalized Expectation Criteria for Bootstrapping Extractors using Record-Text Alignment.” In: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing (EMNLP 2009).

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• ~7 http://scholar.google.com/scholar?q=%22Generalized+Expectation+Criteria+for+Bootstrapping+Extractors+using+Record-Text+Alignment%22+2009

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Abstract

Traditionally, machine learning approaches for information extraction require human annotated data that can be costly and time-consuming to produce. However, in many cases, there already exists a database (DB) with schema related to the desired output, and records related to the expected input text. We present a conditional random field (CRF) that aligns tokens of a given DB record and its realization in text. The CRF model is trained using only the available DB and unlabeled text with generalized expectation criteria. An annotation of the text induced from inferred alignments is used to train an information extractor. We evaluate our method on a citation extraction task in which alignments between DBLP database records and citation texts are used to train an extractor. Experimental results demonstrate an error reduction of 35% over a previous state-of-the-art method that uses heuristic alignments.

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2009 GeneralizedExpectCritforBootstrap...	Kedar Bellare			Generalized Expectation Criteria for Bootstrapping Extractors using Record-Text Alignment			http://www.cs.umass.edu/~kedarb/papers/dbie ge align.pdf