On the equivalence of boolean and weighted searching based on the convertibility of query forms

Angione, Pauline V.

doi:10.1002/asi.4630260207

Cited by 21 publications

(5 citation statements)

References 7 publications

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“…We identified keywords across three relevant categories: female sex workers (FSW), human immunodeficiency virus (HIV), and violence (Violence). The three categories were combined in a query with the structure “FSW HIV Violence ” under a Boolean search algorithm [ 20 ]. Table 1 lists MeSH and TW key words for each category.…”

Section: Methodsmentioning

confidence: 99%

Automating document classification with distant supervision to increase the efficiency of systematic reviews: A case study on identifying studies with HIV impacts on female sex workers

Zhang

Al-Zaidy

et al. 2022

PLoS ONE

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There remains a limited understanding of the HIV prevention and treatment needs among female sex workers in many parts of the world. Systematic reviews of existing literature can help fill this gap; however, well-done systematic reviews are time-demanding and labor-intensive. Here, we propose an automatic document classification approach to a systematic review to significantly reduce the effort in reviewing documents and optimizing empiric decision making. We first describe a manual document classification procedure that is used to curate a pertinent training dataset and then propose three classifiers: a keyword-guided method, a cluster analysis-based method, and a random forest approach that utilizes a large set of feature tokens. This approach is used to identify documents studying female sex workers that contain content relevant to either HIV or experienced violence. We compare the performance of the three classifiers by cross-validation in terms of area under the curve of the receiver operating characteristic and precision and recall plot, and found random forest approach reduces the amount of manual reading for our example by 80%; in sensitivity analysis, we found that even trained with only 10% of data, the classifier can still avoid reading 75% of future documents (68% of total) while retaining 80% of relevant documents. In sum, the automated procedure of document classification presented here could improve both the precision and efficiency of systematic reviews and facilitate live reviews, where reviews are updated regularly. We expect to obtain a reasonable classifier by taking 20% of retrieved documents as training samples. The proposed classifier could also be used for more meaningfully assembling literature in other research areas and for rapid documents screening with a tight schedule, such as COVID-related work during the crisis.

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Section: Methodsmentioning

confidence: 99%

Automating document classification with distant supervision to increase the efficiency of systematic reviews: A case study on identifying studies with HIV impacts on female sex workers

Zhang

Al-Zaidy

et al. 2022

PLoS ONE

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“…Table 1 lists the keywords in three categories: female sex workers (FSW), human immunodeficiency virus (HIV) and violence (Violence). To retrieve articles, key words across the three categories were combined in a query with the structure "FSW AND (HIV OR Violence)" under a Boolean search algorithm [2].…”

Section: Keyword-guided Approachmentioning

confidence: 99%

Automating Document Classification with Distant Supervision to Increase the Efficiency of Systematic Reviews

Li¹,

Al-Zaidy²,

Zhang³

et al. 2020

Preprint

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Objective: Systematic reviews of scholarly documents often provide complete and exhaustive summaries of literature relevant to a research question. However, welldone systematic reviews are expensive, time-demanding, and labor-intensive. Here, we propose an automatic document classification approach to significantly reduce the effort in reviewing documents. Methods: We first describe a manual document classification procedure that is used to curate a pertinent training dataset and then propose three classifiers: a keyword-guided method, a cluster analysis-based refined method, and a random forest approach that utilizes a large set of feature tokens. As an example, this approach is used to identify documents studying female sex workers that are assumed to contain content relevant to either HIV or violence. We compare the performance of the three classifiers by cross-validation and conduct a sensitivity analysis on the portion of data utilized in training the model. Results: The random forest approach provides the highest area under the curve (AUC) for both receiver operating characteristic (ROC) and precision/recall (PR). Analyses of precision and recall suggest that random forest could facilitate manually reviewing 20% of the articles while containing 80% of the relevant cases. Finally, we found a good classifier could be obtained by using a relatively small training sample size. Conclusions:In sum, the automated procedure of document classification presented here could improve both the precision and efficiency of systematic reviews, as well as facilitating live reviews, where reviews are updated regularly.

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“…. provides identical retrieval (the same set of documents) for any given query" (Angione, 1975). Moreover, both approaches could be similar procedurally.…”

Section: Analysis Of the Existing Criticism Of A Boolean Systemmentioning

confidence: 99%

Boolean search: Current state and perspectives

Frants¹,

Shapiro²,

Voiskunskii³

et al. 1999

J. Am. Soc. Inf. Sci.

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Most of the operational information retrieval (IR) systems in existence today useBoolean logic during search. Such systems are usually called Boolean IR systems. These systems, as any other IR systems, are not perfect and the problem of their development (and hence providing better quality service for real users) is one of the most important problems in Information Science. From this viewpoint, the article analyzes existing criticisms of operational systems and points out some of their positive features. At the same time, certain negative effects which hinder the development of existing systems are considered. Finally, the article provides several conclusions about using Boolean logic in developing multiversion IR systems.

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On the equivalence of boolean and weighted searching based on the convertibility of query forms

Cited by 21 publications

References 7 publications

Automating document classification with distant supervision to increase the efficiency of systematic reviews: A case study on identifying studies with HIV impacts on female sex workers

Automating document classification with distant supervision to increase the efficiency of systematic reviews: A case study on identifying studies with HIV impacts on female sex workers

Automating Document Classification with Distant Supervision to Increase the Efficiency of Systematic Reviews

Boolean search: Current state and perspectives

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