The development and empirical study of a literature review aiding system

Chen, Tsung Teng

doi:10.1007/s11192-012-0728-3

Cited by 13 publications

(6 citation statements)

References 20 publications

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“…For instance, users interested in latest developments might prefer recent publications over older ones. Moreover, there are retrieval systems that use citations in articles and co-citations of articles (articles that are often cited together) to visually map literature into clusters of related publications that then can be used for browsing relevant and related papers [Chen, 2012].…”

Section: Sortingmentioning

confidence: 99%

A Hermeneutic Approach for Conducting Literature Reviews and Literature Searches

Boell

Ćećez-Kecmanović²

2014

CAIS

311

324

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The quality and success of scholarly work depends in large measure on the quality of the literature review process. This paper advances conceptual understanding of the literature review process and extends earlier guidelines on literature reviews. It proposes a hermeneutic framework that integrates the analysis and interpretation of literature and the search for literature. This hermeneutic framework describes the literature review process as fundamentally a process of developing understanding that is iterative in nature. Using the hermeneutic circle it describes the literature review process as being constituted by literature searching, classifying and mapping, critical assessment, and argument development. The hermeneutic approach emphasizes continuous engagement with and gradual development of a body of literature during which increased understanding and insights are developed. The paper contributes to better understanding of the literature review process and provides guidelines to assist researchers in conducting high quality reviews. Approaches for efficient searching are included in an Appendix.

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Section: Sortingmentioning

confidence: 99%

A Hermeneutic Approach for Conducting Literature Reviews and Literature Searches

Boell

Ćećez-Kecmanović²

2014

CAIS

311

324

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“…As such, papers ascribed to a factor are treated as the constituent nodes of a document cluster. The factor‐based clustering is among one of several steps to be carried out for the intellectual structure building, which is computerized using Intellectual Structurer (Chen, ). Taking the data set “Text Mining Application” as an illustrative example, 20 factors are generated by the intellectual structure building process.…”

Section: Methodsmentioning

confidence: 99%

“…The threshold values were selected to filter out the less-cited papers (through citation threshold), and augment the structure (via cocitation threshold). The factor-based clustering is among one of several steps to be carried out for the intellectual structure building, which is computerized using Intellectual Structurer (Chen, 2012). The pruned cocitation graphs contain 159 and 215 articles, respectively.…”

Section: Citation-based Approachmentioning

confidence: 99%

The congruity between linkage‐based factors and content‐based clusters—an experimental study using multiple document corpora

Chen

2015

Asso for Info Science & Tech

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Intellectual Structure (IS) is a bibliometric method that is widely applied in knowledge domain analysis and in science mapping. An intellectual structure consists of clusters of related documents ascribed to individual factors. Documents ascribed to a factor are generally associated with a common research theme. As such, the contents of documents ascribed to a factor are theorized to be similar to each other. This study shows that the link-based relatedness implies content-based similarity. The intellectual structures of two research domains were derived from data sets retrieved from the Microsoft Academic Search database. The collection of documents ascribed to a factor is referred to as a factor-based document cluster, which the contentbased document clusters are compared with. All documents in an intellectual structure are re-clustered based on their content similarity, which is derived from the cosine of their vector form encoded in documents' term frequency inverse document frequency (TF-IDF) weighted terms. The factor-based document clusters are then compared with the content-based clusters for congruity. We used the Rand index and kappa coefficient to check the congruity between the factor-based and content-based document clusters. The kappa coefficient indicates that there is fair to moderate agreement between the clusters derived from these two different bases.

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“…Specifically, we rely on previous work by Chen, who employs a psychometric graph scaling method, pathfinder networks (PFNETs), to represent semantic spaces found in a collection of conference proceedings [19,20] that were derived from a similarity matrix of co-authorship occurrences using latent semantic analysis (LSA) and singular value decomposition (SVD). This approach was further explored in more recent contributions [21,22] to build complete systems aiming to support the literature review process. In our past work [8], we employed SVD to propose a similar analysis based on author-assigned keywords that we adapted to this study (see Section 4).…”

Section: Cognitive Data Visualizationmentioning

confidence: 99%

Defragmenting Research Areas with Knowledge Visualization and Visual Text Analytics

Benito-Santos

Therón

2020

Applied Sciences

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The increasing specialization of science is motivating the fragmentation of traditional and well-established research areas into interdisciplinary communities of practice that focus on cooperation between experts to solve problems in a wide range of domains. This is the case of problem-driven visualization research (PDVR), in which groups of scholars use visualization techniques in different application domains such as the digital humanities, bioinformatics, sports science, or computer security. In this paper, we employ the findings obtained during the development of a novel visual text analytics tool we built in previous studies, GlassViz, to automatically detect interesting knowledge associations and groups of common interests between these communities of practice. Our proposed method relies on the statistical modeling of author-assigned keywords to make its findings, which are demonstrated in two use cases. The results show that it is possible to propose interactive, semisupervised visual approaches that aim at defragmenting a body of research using text-based, automatic literature analysis methods.

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The development and empirical study of a literature review aiding system

Cited by 13 publications

References 20 publications

A Hermeneutic Approach for Conducting Literature Reviews and Literature Searches

A Hermeneutic Approach for Conducting Literature Reviews and Literature Searches

The congruity between linkage‐based factors and content‐based clusters—an experimental study using multiple document corpora

Defragmenting Research Areas with Knowledge Visualization and Visual Text Analytics

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