Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Quantum computation and quantum information
Quantum computation and quantum information
Information-geometric measure for neural spikes
Neural Computation
Geometry and Meaning
Lectures on Quantum Information
Lectures on Quantum Information
Information geometry on hierarchy of probability distributions
IEEE Transactions on Information Theory
Distributional memory: A general framework for corpus-based semantics
Computational Linguistics
Using the quantum probability ranking principle to rank interdependent documents
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
An investigation of quantum interference in information retrieval
IRFC'10 Proceedings of the First international Information Retrieval Facility conference on Adbances in Multidisciplinary Retrieval
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An emerging topic in Quantuam Interaction is the use of lexical semantic spaces, as Hilbert spaces, to capture the meaning of words. There has been some initial evidence that the phenomenon of quantum entanglement exists in a semantic space and can potentially play a crucial role in determining the embeded semantics. In this paper, we propose to consider pure high-order entanglements that cannot be reduced to the compositional effect of lower-order ones, as an indicator of high-level semantic entities. To characterize the intrinsic order of entanglements and distinguish pure high-order entanglements from lower-order ones, we develop a set of methods in the framework of Information Geometry. Based on the developed methods, we propose an expanded vector space model that involves context-sensitive high-order information and aims at characterizing high-level retrieval contexts. Some initial ideas on applying the proposed methods in query expansion and text classification are also presented.