How can a trie be used in a search engine(not for autocomplete)?
Putting each word w into a Trie data structure reduces the memory needed to store the words and speeds up a search for a specific word. At the end of each word in the Trie, you'll find a list of pointers to documents that contain the word for which you searched.
I've come across this:

The core information stored by a search engine is a dictionary, called an inverted
  index or inverted file, storing key-value pairs (w,L), where w is a word and L is
  a collection of pages containing word w. The keys (words) in this dictionary are
  called index terms and should be a set of vocabulary entries and proper nouns as
  large as possible. The elements in this dictionary are called occurrence lists and
  should cover as many Web pages as possible.
We can efficiently implement an inverted index with a data structure consisting
  of the following:

An array storing the occurrence lists of the terms (in no particular order).
A compressed trie for the set of index terms, where each leaf stores the index
  of the occurrence list of the associated term.
  The reason for storing the occurrence lists outside the trie is to keep the size of the
  trie data structure sufficiently small to fit in internal memory. Instead, because of
  their large total size, the occurrence lists have to be stored on disk.


and I don't understand it. If a dictionary is used to store occurence lists, what's the purpose of the trie? If I'm going to have to search for the word in the dictionary anyway, why bother with the trie?
Edit: The quote is from Data Structures and Algorithms in Python by Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser