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Xue Wang; Gaoxiang Luo – Society for Research on Educational Effectiveness, 2024
Background: Despite the usefulness of systematic reviews and meta-analyses, they are time-consuming and labor-intensive (Michelson & Reuter, 2019). The technological advancements in recent years have led to the development of tools aimed at streamlining the processes of systematic reviews and meta-analyses. Innovations such as Paperfetcher…
Descriptors: Meta Analysis, Artificial Intelligence, Computational Linguistics, Computer Software
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Thakur, Khusbu; Kumar, Vinit – New Review of Academic Librarianship, 2022
A vast amount of published scholarly literature is generated every day. Today, it is one of the biggest challenges for organisations to extract knowledge embedded in published scholarly literature for business and research applications. Application of text mining is gaining popularity among researchers and applications are growing exponentially in…
Descriptors: Information Retrieval, Data Analysis, Research Methodology, Trend Analysis
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Jonak, Zdenek – Information Processing and Management, 1984
Demonstrates efficiency of preparation of query description using semantic analyser method based on analysis of semantic structure of documents in field of automatic indexing. Results obtained are compared with automatic indexing results performed by traditional methods and results of indexing done by human indexers. Sample terms and codes are…
Descriptors: Algorithms, Automatic Indexing, Comparative Analysis, Information Retrieval
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Griffiths, Alan; And Others – Journal of Documentation, 1984
Considers classifications produced by application of single linkage, complete linkage, group average, and word clustering methods to Keen and Cranfield document test collections, and studies structure of hierarchies produced, extent to which methods distort input similarity matrices during classification generation, and retrieval effectiveness…
Descriptors: Algorithms, Classification, Cluster Analysis, Cluster Grouping
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Willett, Peter – Information Processing and Management, 1981
Describes a fast algorithm for comparing the lists of terms representing documents in automatic classification experiments. Complexity and running time for the algorithm are compared to other procedures, and a short algol-like routine is presented in the appendix. Eight references are included. (Author/BK)
Descriptors: Algorithms, Automatic Indexing, Classification, Documentation