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Conditional Ranking Algorithms for Efficient Object Retrieval and Object Querying on Relational Data

Willem Waegeman, Michiel Stock, Bernard De Baets, Tapio Pahikkala, Antti Airola, Tapio Salakoski, Conditional Ranking Algorithms for Efficient Object Retrieval and Object Querying on Relational Data. In: Thomas Demeester, Johannes Deleu, Laurent Mertens, Dieter Plaetinck, An De Moor, Thong Hoang, Tim Wauters, Chris Develder, Brecht Vermeulen, Piet Demeester (Eds.), Proceedings of the 12th Dutch-Belgian Information Retrieval Workshop (DIR 2012), 59–60, Ghent University, 2012.

Abstract:

In domains like audio, video and document retrieval, bioinformatics, social network analysis and game playing, one can find retrieval tasks where the goal consists of inferring a ranking of objects, conditioned on a particular target object query. We present a general machine learning framework for learning conditional rankings from various types of relational and structured data. In our kernel-based approach, a ranking can be conditioned on unseen object queries and retrieval from symmetric or reciprocal relations can be treated as two important special cases. Furthermore, we propose an efficient algorithm for conditional ranking by optimizing squared regression and ranking loss functions. Experiments on synthetic and real-world data illustrate that such an approach delivers state-of-the-art performance in terms of predictive power and computational complexity. Moreover, we also show empirically that incorporating relational domain knowledge can improve the generalization performance.

BibTeX entry:

@INPROCEEDINGS{inpWaStDePaAiSa12a,
  title = {Conditional Ranking Algorithms for Efficient Object Retrieval and Object Querying on Relational Data},
  booktitle = {Proceedings of the 12th Dutch-Belgian Information Retrieval Workshop (DIR 2012)},
  author = {Waegeman, Willem and Stock, Michiel and De Baets, Bernard and Pahikkala, Tapio and Airola, Antti and Salakoski, Tapio},
  editor = {Demeester, Thomas and Deleu, Johannes and Mertens, Laurent and Plaetinck, Dieter and De Moor, An and Hoang, Thong and Wauters, Tim and Develder, Chris and Vermeulen, Brecht and Demeester, Piet},
  publisher = {Ghent University},
  pages = {59–60},
  year = {2012},
  keywords = {Information retrieval, Machine learning, Ranking},
}

Belongs to TUCS Research Unit(s): Algorithmics and Computational Intelligence Group (ACI), Turku BioNLP Group

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