A domain independent environment for creating information extraction modules

Feldman, Ronen; Aumann, Yonatan; Liberzon, Yair; Ankori, Kfir; Schler, Jonathan; Rosenfeld, Benjamin

doi:10.1145/502585.502699

Cited by 10 publications

(2 citation statements)

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“…Based on actual empirical evaluation, it was found that it is enough to focus just on the core constituents of sentences and use shallow parsing augmented by smart skips. These skips enable the information extraction engine to skip irrelevant parts, and focus just on the important phrases of each sentence (Appelt and Israel, 1999;Feldman et al, 2001;Feldman et al, 2000). Researchers have attempted before to use full parsing as a component in their information systems and have concluded that it was not worthwhile to invest the extra effort.…”

Section: Full Versus Shallow Parsing In Iementioning

confidence: 99%

“…The framework used for implementing the information extraction system is the rule-based general IE language DIAL (declarative information analysis language) (Feldman et al, 2001). Rules in DIAL are sequences of pattern-matching elements, augmented by a set of constraints that matched patterns must satisfy, as well as by a set of assignments to rule's parameters and actions regarding external data structures.…”

Section: Implementation In the Dial Languagementioning

confidence: 99%

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Mining the Biomedical Literature in the Genomic Era: An Overview

Shatkay

Feldman

2003

Journal of Computational Biology

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204

113

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The past decade has seen a tremendous growth in the amount of experimental and computational biomedical data, specifically in the areas of genomics and proteomics. This growth is accompanied by an accelerated increase in the number of biomedical publications discussing the findings. In the last few years, there has been a lot of interest within the scientific community in literature-mining tools to help sort through this abundance of literature and find the nuggets of information most relevant and useful for specific analysis tasks. This paper provides a road map to the various literature-mining methods, both in general and within bioinformatics. It surveys the disciplines involved in unstructured-text analysis, categorizes current work in biomedical literature mining with respect to these disciplines, and provides examples of text analysis methods applied towards meeting some of the current challenges in bioinformatics.

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Section: Full Versus Shallow Parsing In Iementioning

confidence: 99%

Section: Implementation In the Dial Languagementioning

confidence: 99%