Recursive descent parsing for Boolean grammars

Okhotin, Alexander

doi:10.1007/s00236-007-0045-0

Cited by 21 publications

(9 citation statements)

References 18 publications

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“…The next stage is to define the exposed/case group as the system assigns each patient an index date based on single or multiple exposure (Table 2). In this step we employ a recursive descent parser (a mathematical tool used to determine if a sequence of symbols such as sentence is syntactically correct) [38], and a regular grammar (set of rules used to define the syntax for a particular language) [39] to successfully identify any number of exposures. If the study has more than one exposure, then we propose two modes of parsing namely strict parsing and loose parsing.…”

Section: Stage 2: Defining the Exposed Group In Cohort Design Or Casementioning

confidence: 99%

Data extraction for epidemiological research (DExtER): a novel tool for automated clinical epidemiology studies

et al. 2020

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The use of primary care electronic health records for research is abundant. The benefits gained from utilising such records lies in their size, longitudinal data collection and data quality. However, the use of such data to undertake high quality epidemiological studies, can lead to significant challenges particularly in dealing with misclassification, variation in coding and the significant effort required to pre-process the data in a meaningful format for statistical analysis. In this paper, we describe a methodology to aid with the extraction and processing of such databases, delivered by a novel software programme; the "Data extraction for epidemiological research" (DExtER). The basis of DExtER relies on principles of extract, transform and load processes. The tool initially provides the ability for the healthcare dataset to be extracted, then transformed in a format whereby data is normalised, converted and reformatted. DExtER has a user interface designed to obtain data extracts specific to each research question and observational study design. There are facilities to input the requirements for; eligible study period, definition of exposed and unexposed groups, outcome measures and important baseline covariates. To date the tool has been utilised and validated in a multitude of settings. There have been over 35 peer-reviewed publications using the tool, and DExtER has been implemented as a validated public health surveillance tool for obtaining accurate statistics on epidemiology of key morbidities. Future direction of this work will be the application of the framework to linked as well as international datasets and the development of standardised methods for conducting electronic pre-processing and extraction from datasets for research purposes.

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Section: Stage 2: Defining the Exposed Group In Cohort Design Or Casementioning

confidence: 99%

Data extraction for epidemiological research (DExtER): a novel tool for automated clinical epidemiology studies

et al. 2020

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“…For every strongly non-left-recursive grammar, the corresponding system of equations (2) has a unique solution [7]. Then, for every…”

Section: In a Strongly Non-left-recursive Grammar It Is Possible To Dmentioning

confidence: 99%

“…For every nonterminal A ∈ Σ, the corresponding procedure A() [7] chooses a rule using the parsing table and then proceeds checking the conjuncts one by one. The code for this procedure is defined as follows:…”

Section: In a Strongly Non-left-recursive Grammar It Is Possible To Dmentioning

confidence: 99%

“…The extended expressive power of Boolean grammars and their intuitive clarity make them a much more powerful tool for specifying languages than the context-free grammars. Another important fact is that the main context-free parsing algorithms, such as the Cocke-Kasami-Younger, the recursive descent and the generalized LR, can be extended to Boolean grammars without an increase in computational complexity [6,8,7].…”

Section: Introductionmentioning

confidence: 99%

“…The purpose of this paper is to establish some limitations of the expressive power of the subcase of Boolean grammars to which the recursive descent parsing is applicable: the LL(k) Boolean grammars [7]. Already for this class, obtaining nonrepresentability proofs presents a challenge: consider that there exists an LL(1) linear conjunctive grammar for the language of computations of any Turing machine, which rules out a general pumping lemma.…”

Section: Introductionmentioning

confidence: 99%

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