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SIGIR
2009
ACM

Portfolio theory of information retrieval

11 years 8 months ago
Portfolio theory of information retrieval
This paper studies document ranking under uncertainty. It is tackled in a general situation where the relevance predictions of individual documents have uncertainty, and are dependent between each other. Inspired by the Modern Portfolio Theory, an economic theory dealing with investment in financial markets, we argue that ranking under uncertainty is not just about picking individual relevant documents, but about choosing the right combination of relevant documents. This motivates us to quantify a ranked list of documents on the basis of its expected overall relevance (mean) and its variance; the latter serves as a measure of risk, which was rarely studied for document ranking in the past. Through the analysis of the mean and variance, we show that an optimal rank order is the one that balancing the overall relevance (mean) of the ranked list against its risk level (variance). Based on this principle, we then derive an efficient document ranking algorithm. It generalizes the well-kno...
Jun Wang, Jianhan Zhu
Added 28 May 2010
Updated 28 May 2010
Type Conference
Year 2009
Where SIGIR
Authors Jun Wang, Jianhan Zhu
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