We explore the relationship between time and relevance using TREC ad-hoc queries. A type of query is identified that favors very recent documents. We propose a time-based language model approach to retrieval for these queries. We show how time can be incorporated into both query-likelihood models and relevance models. These models were used for experiments comparing time-based language models to heuristic techniques for incorporating document recency in the ranking. Our results show that time-based models perform as well as or better than the best of the heuristic techniques.
Li and Croft REF were the first that proposed a time-based language model to boost the ranking of more recent results.
Time-based language models
CIKM '03
Computer Science