Each kind of document possesses its special classification problems. When not otherwise specified, text classification is implied. Documents may be classified according to their subjects or according to other attributes such as document type, author, printing year etc.
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In the rest of this article only subject classification is considered. There are two main philosophies of subject classification of documents: the content-based approach and the request-based approach. Content-based classification is classification in which the weight given to particular subjects in a document determines the class to which the document is assigned.
Request-oriented classification or -indexing is classification in which the anticipated request from users is influencing how documents are being classified.
Request-oriented classification may be classification that is targeted towards a particular audience or user group. It is probably better, however, to understand request-oriented classification as policy-based classification : The classification is done according to some ideals and reflects the purpose of the library or database doing the classification.
In this way it is not necessarily a kind of classification or indexing based on user studies. Only if empirical data about use or users are applied should request-oriented classification be regarded as a user-based approach. Sometimes a distinction is made between assigning documents to classes "classification" versus assigning subjects to documents " subject indexing " but as Frederick Wilfrid Lancaster has argued, this distinction is not fruitful.
The view that this distinction is purely superficial is also supported by the fact that a classification system may be transformed into a thesaurus and vice versa cf.
Therefore, is the act of labeling a document say by assigning a term from a controlled vocabulary to a document at the same time to assign that document to the class of documents indexed by that term all documents indexed or classified as X belong to the same class of documents. Automatic document classification tasks can be divided into three sorts: supervised document classification where some external mechanism such as human feedback provides information on the correct classification for documents, unsupervised document classification also known as document clustering , where the classification must be done entirely without reference to external information, and semi-supervised document classification ,  where parts of the documents are labeled by the external mechanism.
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Taxonomy of Australian Mammals, Stephen Jackson, Colin Groves,
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Ubiquity Press books and articles are typeset by SiliconChips and Diacritech. This process involves them receiving the book and book associated metadata and contacting the authors to finalise the layout. A complete taxonomic revision of all Australian mammals, both terrestrial and marine. Reviews Details Features Contents Authors Reviews "this is a must-have book for systematists interested in the biodiversity of vertebrates of the southern hemisphere.
Features Includes all ranks of Australian mammals and includes the synonyms for each rank Easy reference to all species, subspecies and synonyms of all Australian mammals both native and introduced Complete bibliography to promote further reading and research Large list of definitions of terms used in the text Highlights areas where future taxonomic research is needed There are some minor errors on pages 22, 26, , , and that should be replaced with these entries.
Contents Introduction Acknowledgements Definitions of nomenclatural and bibliographic terms Abbreviations Taxonomy of the mammals of Australia References Appendix Index of common names Index of scientific names. He has studied different aspects of Australian mammals over the last 20 years from which he has published numerous refereed papers and book chapters.
This is his sixth book. He works primarily on mammalian taxonomy and phylogeny, mainly on ungulates, primates and carnivores, and has also published occasional papers on monotremes, marsupials and rodents.