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MUSY 301: Introduction to Music Research and Writing (2024)

LC and Dewey Subject Browsing Map

 

Natural language vs Keyword vs LCSH

Natural language searching

A natural language search is a search using regular spoken language, such as English. Using this type of search, you can ask the database a question or type in a sentence that describes the information you are looking for.

Keyword searching is how you typically search web search engines.  Think of important words or phrases and type them in to get results.

Subject headings describe the content of each item in a database. Use these headings to find relevant items on the same topic.  Searching by subject headings (a.k.a. descriptors) is the most precise way to search article databases.

It is not easy to guess which subject headings are used in a given database. For example, the phone book's Yellow Pages use subject headings. If you look for "Movie Theatres" you will find nothing, as they are listed under the subject heading "Theatres - Movies."

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A subject heading is a specific word or phrase used to find and organize books and articles by topic. Subject headings can be a great way to easily find things related directly to your topic.  Once you have identified a book or article that is worthwhile, look at the subject headings, and you can click directly on the subject heading to get a list of books on the same subject.

Subject headings are different from keywords in that they are specific terms assigned to a subject by an organization. For example, the Library of Congress supplies subject headings for books owned by Oberlin College (and other libraries), and the company that provides Music Index supplies subject headings for the articles indexed in that database.

Keywords

vs.

Subjects

  • natural language words describing your topic - good to start with
 
  • pre-defined "controlled vocabulary" words used to describe the content of each item (book, journal article) in a database
  • more flexible to search by - can combine together in many ways
 
  • less flexible to search by - need to know the exact controlled vocabulary term
  • database looks for keywords anywhere in the record - not necessarily connected together
 
  • database looks for subjects only in the subject heading or descriptor field, where the most relevant words appear
  • may yield too many or too few results
 
  • if too many results - also uses subheadings to focus on one aspect of the broader subject
  • may yield many irrelevant results
 
  • results usually very relevant to the topic