OpenAIR OpenAIR
 
 

OpenAIR @ RGU >
Design and Technology >
Computing >
Conference publications (Computing) >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10059/396
This item has been viewed 15 times in the last year. View Statistics

Files in This Item:

File Description SizeFormat
Song Quantum Interaction 2009.pdf338.69 kBAdobe PDFView/Open
Title: Characterizing pure high-order entanglements in lexical semantic spaces via information geometry.
Authors: Hou, Yuexian
Song, Dawei
Editors: Bruza, Peter D.
Sofge, Donald
Lawless, William
Van Rijsbergen, C. J.
Klusch, Matthias
Keywords: Information geometry
Pure high-order entanglement
Semantic emergence
Extended vector model
Issue Date: Apr-2009
Publisher: Springer
Citation: HOU, Y., and SONG, D., 2009. Characterizing pure high-order entanglements in lexical semantic spaces via information geometry. In: P. BRUZA et al., eds. Quantum Interaction: Third International Symposium,QI 2009, Saarbrucken, Germany, March 2009, Proceedings. 25-27 March. Berlin: Springer. pp. 237-250.
Series/Report no.: LNAI
5494
Abstract: 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.
ISBN: 9783642008337
Appears in Collections:Conference publications (Computing)

All items in OpenAIR are protected by copyright, with all rights reserved.

 

 
   Disclaimer | Freedom of Information | Privacy Statement |Copyright ©2012 Robert Gordon University, Schoolhill, Aberdeen, AB10 1FR, Scotland, UK: a Scottish charity, registration No. SCO13781