  Query autocompletions help users of search engines to speed up their searches
by recommending completions of partially typed queries in a drop down box.
These recommended query autocompletions are usually based on large logs of
queries that were previously entered by the search engine's users. Therefore,
misinformation entered -- either accidentally or purposely to manipulate the
search engine -- might end up in the search engine's recommendations,
potentially harming organizations, individuals, and groups of people. This
paper proposes an alternative approach for generating query autocompletions by
extracting anchor texts from a large web crawl, without the need to use query
logs. Our evaluation shows that even though query log autocompletions perform
better for shorter queries, anchor text autocompletions outperform query log
autocompletions for queries of 2 words or more.
