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information retrieval

information retrieval. wed sept 02 2015 data…. -start at 6.45. framework for today ’ s lecture…. STRUCTURED vs unstructured data. easy to envision structured data in terms of “ tables ”. Employee. Manager. Salary. Smith. Jones. 68000. Chang. Smith. 65000. Ivy. Smith. 50000.

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information retrieval

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  1. information retrieval wed sept 02 2015 data…

  2. -start at 6.45

  3. framework for today’s lecture…

  4. STRUCTUREDvs unstructured data easy to envision structured data in terms of “tables” Employee Manager Salary Smith Jones 68000 Chang Smith 65000 Ivy Smith 50000 Typically allows numerical range and exact match (for text) queries, e.g., Salary < 60000 AND Manager = Smith.

  5. tables in a MS Access relational database – defines each defining a social networking site

  6. Data entry form in a MS Access relational database – create each record

  7. structured vsUNSTRUCTURED data • typically refers to free text • email is a good example of unstructured data. it's indexed by date, time, sender, recipient, and subject, but the body of an email remains unstructured • other examples of unstructured data include books, documents, medical records, and social media posts

  8. magazine article is an example of unstructured data

  9. Document collection (corpus) Query Representation function Representation function Matching function Index CATEGORIES SUBJECT HEADINGS Results

  10. KWIC Key word in context

  11. KWIC Key word in context

  12. metadata metadata

  13. What is Metadata? • Classic definition: data about data • Metadata is structured information that describes, explains, locates, or otherwise makes it easier to retrieve, use, or manage an information resource. (NISO) • 3 primary “types”: • Descriptive • Structural • Administrative (rights management, preservation)

  14. digital forensics

  15. This reading really made me think about how easily accessible and organized information is today because of the implementation of metadata. It sparked a few questions: Without metadata, how would accessing data, resources and information be different in today’s society? -Chris

  16. More Metadata: A Cataloging Record http://search.lib.unc.edu/search?R=UNCb7097376

  17. The Idea of Facets • Facets are a way of labeling data • A kind of Metadata (data about data) • Can be thought of as properties of items • Facets vs. Categories • Items are placed INTO a category system • Multiple facet labels are ASSIGNED TO items

  18. Facets Epicurious example http://www.epicurious.com/ • Create INDEPENDENT categories (facets) • Each facet has labels (sometimes arranged in a hierarchy) • Assign labels from the facets to every item • Example: recipe collection Ingredient Cooking Method Chicken Bell Pepper Stir-fry Curry Course Cuisine Main Course Thai

  19. The Idea of Facets • Break out all the important concepts into their own facets • Sometimes the facets are hierarchical • Assign labels to items from any level of the hierarchy Preparation Method Fry Saute Boil Bake Broil Freeze Desserts Cakes Cookies Dairy Ice Cream Sorbet Flan Fruits Cherries Berries Blueberries Strawberries Bananas Pineapple

  20. Using Facets • Now there are multiple ways to get to each item Preparation Method Fry Saute Boil Bake Broil Freeze Desserts Cakes Cookies Dairy Ice Cream Sherbet Flan Fruits Cherries Berries Blueberries Strawberries Bananas Pineapple Fruit > Pineapple Dessert > Cake Preparation > Bake Dessert > Dairy > Sherbet Fruit > Berries > Strawberries Preparation > Freeze

  21. labor intensive? expensive?

  22. UNC Libraries Online Catalog http://www.lib.unc.edu/ e.g. personal crisis

  23. caveat: semi-structured data • in fact almost no data is absolutely “unstructured” • e.g., this slide has distinctly identified zones such as the title and bullets • facilitates “semi-structured” search such as • title contains data and bullets contain structure

  24. Let’s look at a database of magazine & journal articles… …Academic Search Complete >> UNC Libraries Homepage: http://www.lib.unc.edu/ >> E-Research by Discipline >> Frequently Used >> Academic Search Premier [off-campus log in with onyen/password]

  25. Organization / Search • We organize to enable retrieval • The more effort we put into organizing information, the more effectively it can be retrieved • The more effort we put into retrieving information, the less it needs to be organized first • We need to think in terms of investment, allocation of costs and benefits between the organizer and retriever • The allocation differs according to the relationship between them; who does the work and who gets the benefit?

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