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- Understanding of works and granularity at which links between items should be understood to understand importance
- Deal with questions of how to work in a rather data sparse environment -- how to merge information from page-rank like ordering with some other order that doesn’t rely on a dense graph
- Will need to do iterative/experimental work on what will influence rank. Possibilities include:
- e.g., a Libguide that cites a work -- ideally with an OCLC number or DOI
- could scrape links into the catalog
- usage data
- external ranking
- e.g., a Libguide that cites a work -- ideally with an OCLC number or DOI
- Will need to do iterative/experimental work on what will influence rank. Possibilities include:
- Might use various axes of similarity: Example -- Griffin Weber’s analysis that is performed nightly and stored in the triple store in a different namespace -- geographic proximity, association with MeSH terms calculated from occurrence in publications
Who will do what?
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