information retrieval thur jan data…

framework for today’s lecture…

STRUCTURED vs unstructured data easy to envision structured data in terms of “tables” 4 EmployeeManagerSalary SmithJones50000 ChangSmith IvySmith Typically allows numerical range and exact match (for text) queries, e.g., Salary < AND Manager = Smith.

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

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

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

magazine article is an example of unstructured data

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

KWIC Key word in context

KWIC Key word in context

metadata

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)

b More Metadata: A Cataloging Record

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

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

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

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

UNC Libraries Online Catalog

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

Let’s look at a database of magazine & journal articles… …Academic Search Complete >> UNC Libraries Homepage: >> E-Research Tools >> Frequently Used >> Academic Search Complete [off-campus log in with onyen/password

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?