An adaptive contextual quantum language model

Jingfei Li, Peng Zhang, Dawei Song, Yuexian Hou
2016 Physica A: Statistical Mechanics and its Applications  
Please cite this article as: J. Li, P. Zhang, D. Song, Y. Hou, An adaptive contextual quantum language model, Physica A (2016), http://dx.Abstract User interactions in search system represent a rich source of implicit knowledge about the user's cognitive state and information need that continuously evolves over time. Despite of massive efforts that have been made to exploiting and incorporating this implicit knowledge in information retrieval, it is still a challenge to effectively capture the
more » ... erm dependencies and the user's dynamic information need (reflected by query modifications) in the context of user interaction. To tackle these issues, motivated by the recent Quantum Language Model (QLM), we develop a QLM based retrieval model for session search, which naturally incorporates the complex term dependencies occurring in user's historical queries and clicked documents with density matrices. In order to capture the dynamic information within users' search session, we propose a density matrix transformation framework and further develop an adaptive QLM ranking model. Extensive comparative experiments show the effectiveness of our session quantum language models. the frequency as its value, while in the QLM, the phrase is represented as a 2order density matrix. The values of diagonal elements denote the weights of each single word, and the non-diagonal elements denote the relationship between two single words. It can be observed that the matrix representation of the phrase "information retrieval" contains more information about the inner dependency 60 of the phrase "information retrieval". Furthermore, the ranking function for a Highlights
doi:10.1016/j.physa.2016.03.003 fatcat:jkk5rmfpkfdtpol2kqfr7msw4e