Evaluation of an inference network-based retrieval model
ACM Transactions on Information Systems (TOIS) - Special issue on research and development in information retrieval
The effect multiple query representations on information retrieval system performance
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Two-stage language models for information retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
A logic for uncertain probabilities
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Language Modeling for Information Retrieval
Language Modeling for Information Retrieval
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
Retrieval evaluation with incomplete information
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
The Turn: Integration of Information Seeking and Retrieval in Context (The Information Retrieval Series)
A polyrepresentational approach to interactive query expansion
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
A Belief Model of Query Difficulty That Uses Subjective Logic
ICTIR '09 Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory
Query polyrepresentation for ranking retrieval systems without relevance judgments
Journal of the American Society for Information Science and Technology
Supporting polyrepresentation in a quantum-inspired geometrical retrieval framework
Proceedings of the third symposium on Information interaction in context
A subjective logic formalisation of the principle of polyrepresentation for information needs
Proceedings of the third symposium on Information interaction in context
Developing a test collection for the evaluation of integrated search
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
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According to the principle of polyrepresentation, retrieval accuracy may improve through the combination of multiple and diverse information object representations about e.g. the context of the user, the information sought, or the retrieval system [9, 10]. Recently, the principle of polyrepresentation was mathematically expressed using subjective logic [12], where the potential suitability of each representation for improving retrieval performance was formalised through degrees of belief and uncertainty [15]. No experimental evidence or practical application has so far validated this model. We extend the work of Lioma et al. (2010) [15], by providing a practical application and analysis of the model. We show how to map the abstract notions of belief and uncertainty to real-life evidence drawn from a retrieval dataset. We also show how to estimate two different types of polyrepresentation assuming either (a) independence or (b) dependence between the information objects that are combined. We focus on the polyrepresentation of different types of context relating to user information needs (i.e. work task, user background knowledge, ideal answer) and show that the subjective logic model can predict their optimal combination prior and independently to the retrieval process.