, FOR EXAMPLE, ASSUME THAT IF QUERIES CON-TAINING ONE TERM OFTEN...

2002), for example, assume that if queries con-

taining one term often result in the selection of

(Cui et al., 2005) describe a fuzzy depen-

dency relation matching approach to passage re-

documents containing another term, then a strong

relationship between the two terms exist. In their

trieval in QA. Here, the authors present a statis-

approach, query terms and document terms are

tical technique to measure the degree of overlap

linked via sessions in which users click on doc-

between dependency relations in candidate sen-

uments that are presented as results for the query.

tences with their corresponding relations in the

(Riezler and Liu, 2010) apply a Statistical Ma-

question. Question/answer passage pairs from

TREC-8 and TREC-9 evaluations are used as

chine Translation model to parallel data consist-

ing of user queries and snippets from clicked web

training data. As in some of the papers mentioned

documents and in such a way extract contextual

earlier, a statistical translation model is used, but

expansion terms from the query rewrites.

this time to learn relatedness between paths. (Cui

We see our work as addressing the same fun-

et al., 2004) apply the same idea to answer ex-

traction. In each sentences returned by the IR