Biterm language models for document retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
A Markov random field model for term dependencies
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Automatic feature selection in the markov random field model for information retrieval
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Integrating Proximity to Subjective Sentences for Blog Opinion Retrieval
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Learning concept importance using a weighted dependence model
Proceedings of the third ACM international conference on Web search and data mining
Exploiting query reformulations for web search result diversification
Proceedings of the 19th international conference on World wide web
An evaluation and analysis of incorporating term dependency for ad-hoc retrieval
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Key concepts identification and weighting in search engine queries
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Learning models for ranking aggregates
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Parameterized concept weighting in verbose queries
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Automatic refinement of patent queries using concept importance predictors
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Modeling higher-order term dependencies in information retrieval using query hypergraphs
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Exploiting term dependence while handling negation in medical search
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
On the usefulness of query features for learning to rank
Proceedings of the 21st ACM international conference on Information and knowledge management
Efficient and effective retrieval using selective pruning
Proceedings of the sixth ACM international conference on Web search and data mining
Two-Stage learning to rank for information retrieval
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Pseudo test collections for training and tuning microblog rankers
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
About learning models with multiple query-dependent features
ACM Transactions on Information Systems (TOIS)
Learning to rank query suggestions for adhoc and diversity search
Information Retrieval
The whens and hows of learning to rank for web search
Information Retrieval
Indexing Word Sequences for Ranked Retrieval
ACM Transactions on Information Systems (TOIS)
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Term dependency, or co-occurrence, has been studied in language modelling, for instance by Metzler & Croft who showed that retrieval performance could be significantlyenhanced using term dependency information. In this work, weshow how term dependency can be modelled within the Divergence From Randomness (DFR) framework. We evaluate our term dependency model on the two adhoc retrieval tasks using the TREC .GOV2 Terabyte collection. Furthermore, we examine the effect of varying the term dependency window size on the retrieval performance of the proposed model. Our experiments show that term dependency can indeed besuccessfully incorporated within the DFR framework.