Abstract
The problem of selecting the proper set of questions plays very important role in the domain of information retrieval, e.g., on the Internet, or about requirements during the business interview. In this work we propose a novel approach for selecting the sequence of binary questions to be asked to identify an unknown concept. This solution makes use of Restricted Boltzmann Machine (RBM) as a universal approximator of the distribution over the observable variables. The main idea of the proposed approach is to use RBM to determine transition probabilities in the evolving random process for finding the most suitable question to be selected. We evaluate the proposed approach on two reference datasets.
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Notes
- 1.
Usually up to 20 questions. For that reason the game is called 20 questions game.
- 2.
In this text we associate the issue of discovering the values of features with problem of asking binary questions about the properties of the concepts.
- 3.
In some cases asking about the same thing more than once might be necessary, e.g., when a question is ambiguous and the answer cannot be correctly answered. However, we leave this issue for further research.
- 4.
Each of the elements of vector \( \pi \) is greater or equal 0.
- 5.
Two nominal features from the initial dataset were transformed to binary attributes.
- 6.
It was impossible to correctly distinguish all of the species with the given set of features.
- 7.
The dataset was initially used to detect e-mails with conference announcements.
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Acknowledgments
The research presented in this paper was partially supported by the European Union within the European Regional Development Fund program Number POIG.01.03.01-02-079/12.
© 2014 California Institute of Technology. Government sponsorship acknowledged.
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Zięba, M., Tomczak, J.M., Brzostowski, K. (2015). Selecting right questions with Restricted Boltzmann Machines. In: Selvaraj, H., Zydek, D., Chmaj, G. (eds) Progress in Systems Engineering. Advances in Intelligent Systems and Computing, vol 366. Springer, Cham. https://doi.org/10.1007/978-3-319-08422-0_34
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