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Automatic Indexing of Documents from Journal Descriptors: A Preliminary Investigation
1Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD 20894.
Journal of the American Society for Information Science. American Society for Information Science
|June 30, 2011
Summary
A novel automated document indexing method uses journal descriptors (JDs) for topical categorization. This approach bypasses extensive manual indexing, enabling efficient searching and improved information retrieval.
Area of Science:
- Bibliometrics
- Information Science
- Computational Linguistics
Background:
- Traditional document indexing relies heavily on manual efforts, which is time-consuming and costly.
- Existing methods often require large, pre-indexed training datasets, limiting scalability.
- The need for efficient and automated methods for topical categorization of diverse documents is growing.
Purpose of the Study:
- To introduce a fully automated approach for document indexing.
- To leverage journal-level indexing (journal descriptors - JDs) for topical categorization.
- To enable efficient searching and refinement of results for various document types.
Main Methods:
- Developed an automated system associating textwords from a training set of bibliographic citations with journal indexing.
- Created a consistent and timely set of journal descriptors (JDs) for individual journals.
- Maintained journal indexing within a serials authority database.
Main Results:
- The training set is independent of previous manual document indexing, reducing reliance on extensive historical data.
- The approach requires a smaller intellectual effort focused on journal-level indexing.
- Potential for topical categorization of documents beyond the training set, including articles, monographs, and web documents.
Conclusions:
- This automated journal descriptor (JD) indexing offers a scalable and efficient alternative to manual document indexing.
- JD indexing can provide general subject domain categorization, enhancing search result refinement.
- The method promises improved information retrieval across a wide range of published and grey literature.
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