Formal models for expert finding in enterprise corpora
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Voting for candidates: adapting data fusion techniques for an expert search task
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
AdaRank: a boosting algorithm for information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Incorporating term dependency in the dfr framework
SIGIR '07 Proceedings of the 30th 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
Retrieval and feedback models for blog feed search
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Bloggers as experts: feed distillation using expert retrieval models
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Key blog distillation: ranking aggregates
Proceedings of the 17th ACM conference on Information and knowledge management
On perfect document rankings for expert search
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Predicting the Usefulness of Collection Enrichment for Enterprise Search
ICTIR '09 Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory
Learning to Rank for Information Retrieval
Foundations and Trends in Information Retrieval
The influence of the document ranking in expert search
Proceedings of the 18th ACM conference on Information and knowledge management
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Learning Aggregation Functions for Expert Search
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
A learned approach for ranking news in real-time using the blogosphere
SPIRE'11 Proceedings of the 18th international conference on String processing and information retrieval
Foundations and Trends in Information Retrieval
Learning joint query interpretation and response ranking
Proceedings of the 22nd international conference on World Wide Web
Expertise retrieval in bibliographic network: a topic dominance learning approach
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Quality biased thread retrieval using the voting model
Proceedings of the 18th Australasian Document Computing Symposium
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Aggregate ranking tasks are those where documents are not the final ranking outcome, but instead an intermediary component. For instance, in expert search, a ranking of candidate persons with relevant expertise to a query is generated after consideration of a document ranking. Many models exist for aggregate ranking tasks, however obtaining an effective and robust setting for different aggregate ranking tasks is difficult to achieve. In this work, we propose a novel learned approach to aggregate ranking, which combines different document ranking features as well as aggregate ranking approaches. We experiment with our proposed approach using two TREC test collections for expert and blog search. Our experimental results attest the effectiveness and robustness of a learned model for aggregate ranking across different settings