2. The method of claim 1 , further comprising: determining a distributional similarity score between the first query and the second query, the determination of the distributional similarity score between the first query and a second query being based on a comparison of first frequencies of terms that co-occur in text with terms of the first query and second frequencies of terms that co-occur in text with terms of the second query, wherein computing a similarity score for the first query and a second query comprises providing, as input to a trained model, the distributional similarity score between the first query and each second query and the temporal correlation score between the first query and the second query.
1. A computer-implemented method performed by data processing apparatus, the method comprising: receiving a first query and a plurality of second queries; determining a temporal correlation score between the first query and each second query based on a comparison of a temporal series of occurrences of elements of the first query in a first corpus comprising a first document of a first document type and a temporal series of occurrences of elements of the second query in a second different textual corpus comprising a second document of a second document type that differs from the first document type, wherein the comparison is based on the first document and the second document having timestamps in a same time period; computing a similarity score for the first query and a second query, the similarity score between the first query and a second query being computed based on the temporal correlation score between the first document and the second document; and ranking the second query according to the similarity score.