Leveraging semantically similar queries for ranking via combining representations

• URL: http://arxiv.org/abs/2106.12621v1
• Date: Wed, 23 Jun 2021 18:36:20 GMT
• Title: Leveraging semantically similar queries for ranking via combining representations
• Authors: Hayden S. Helm and Marah Abdin and Benjamin D. Pedigo and Shweti Mahajan and Vince Lyzinski and Youngser Park and Amitabh Basu and Piali~Choudhury and Christopher M. White and Weiwei Yang and Carey E. Priebe
• Abstract summary: In data-scarce settings, the amount of labeled data available for a particular query can lead to a highly variable and ineffective ranking function. One way to mitigate the effect of the small amount of data is to leverage information from semantically similar queries. We describe and explore this phenomenon in the context of the bias-variance trade off and apply it to the data-scarce settings of a Bing navigational graph and the Drosophila larva connectome.
• Score: 20.79800117378761
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In modern ranking problems, different and disparate representations of the items to be ranked are often available. It is sensible, then, to try to combine these representations to improve ranking. Indeed, learning to rank via combining representations is both principled and practical for learning a ranking function for a particular query. In extremely data-scarce settings, however, the amount of labeled data available for a particular query can lead to a highly variable and ineffective ranking function. One way to mitigate the effect of the small amount of data is to leverage information from semantically similar queries. Indeed, as we demonstrate in simulation settings and real data examples, when semantically similar queries are available it is possible to gainfully use them when ranking with respect to a particular query. We describe and explore this phenomenon in the context of the bias-variance trade off and apply it to the data-scarce settings of a Bing navigational graph and the Drosophila larva connectome.

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