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Abstract

Indexing images has always been problematic due to their richness of content and innate subjectivity. Three traditional approaches to indexing images are described and analyzed. An introduction of the contemporary use of social tagging is presented along with its limitations. Traditional practices can continue to be used as a stand-alone solution, however deficiencies limit retrieval. A collaborative technique is supported by current research and a model created by the authors for its inception is explored. CONTENTdm® is used as an example to illustrate tools that can help facilitate this process. Another potential solution discussed is the expansion of algorithms used in computer extraction to include the input and influence of human indexer intelligence. Further research is recommended in each area to discern the most effective method.

About Author

Lindsay Marlow is a recent graduate in Masters of Library and Information Studies from the University at Buffalo, The State University of New York. Her research interests include information retrieval, reference in the digital age, and media &marketing. She hopes to find an academic library position or work within a special library.

Amy Miller plans on completing her Masters program in Library and Information Studies at the University at Buffalo, The State University of New York this winter. Her research interests include information retrieval, the digital divide, and digital libraries. She hopes to find an archives or an academic library position.

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