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Uprety, Sagar; Su, Yi; Song, Dawei and Li, Jingfei
(2018).
DOI: https://doi.org/10.1145/3209978.3210130
Abstract
It has been shown that relevance judgment of documents is influenced by multiple factors beyond topicality. Some multidimensional user relevance models (MURM) proposed in literature have investigated the impact of different dimensions of relevance on user judgment. Our hypothesis is that a user might give more importance to certain relevance dimensions in a session which might change dynamically as the session progresses. This motivates the need to capture the weights of different relevance dimensions using feedback and build a model to rank documents for subsequent queries according to these weights. We propose a geometric model inspired by the mathematical framework of Quantum theory to capture the user's importance given to each dimension of relevance and test our hypothesis on data from a web search engine and TREC Session track.
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- Item ORO ID
- 55725
- Item Type
- Conference or Workshop Item
- ISBN
- 1-4503-5657-5, 978-1-4503-5657-2
- Project Funding Details
-
Funded Project Name Project ID Funding Body Research and Innovation Programme Marie Sklodowska-Curie grant agreement No 721321 European Union Horizon 2020 - Keywords
- Information Retrieval; User modeling; Multidimensional Relevance
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Copyright Holders
- © 2018 ACM
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