Learning in a pairwise term-term proximity framework for information retrieval

摘要

Traditional ad hoc retrieval models do not take into account the closeness or proximity of terms. Document scores in these models are primarily based on the occurrences or non-occurrences of query-terms considered independently of each other. Intuitively, documents in which query-terms occur closer together should be ranked higher than documents in which the query-terms appear far apart.