Score-Safe Term Dependency Processing With Hybrid Indexes
M Petri, A Moffat, JS Culpepper
Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval | ACM Press | Published : 2014
Score-safe index processing has received a great deal of attention over the last two decades. By pre-calculating maximum term impacts during indexing, the number of scoring operations can be minimized, and the top-k documents for a query can be located efficiently. However, these methods often ignore the importance of the effectiveness gains possible when using sequential dependency models. We present a hybrid approach which leverages score-safe processing and suffix-based self-indexing structures in order to provide efficient and effective top-k document retrieval. Copyright 2014 ACM.
Awarded by Australian Research Council
Awarded by ARC DECRA Research Fellowship
This work was supported in part by the Australian Research Council (DP110101743). Shane Culpepper is the recipient of an ARC DECRA Research Fellowship (DE140100275). Simon Gog designed and implemented the pruned suffix tree used in the experiments and integrated it into the IR framework.