In Bag of Tricks for Efficient Text Classification paper which is popular right now, he calculates prec@1 for the datasets in the experimentation segment. What does that mean?
Its "Precision at 1", or how often the highest ranked document is relevant:
Suppose you are looking for items about monkeys. Your query engine queries documents for "monkeys" and ranks by relevance. If the highest ranked document is indeed about monkeys, then that's a win for your query algorithm. But if the highest ranked document is ranked 1 because it has the text "Enough of your monkey business" then its a loss, because that's not really about monkeys.
Repeat over a bunch of search terms. The Precision-at-one is then the number of wins over the total number of search terms tried.