To promote information service ability of digital libraries, a browsing and searching personalized recommendation framework based on the use of ontology is described, where the advantages of ontology are exploited in ...To promote information service ability of digital libraries, a browsing and searching personalized recommendation framework based on the use of ontology is described, where the advantages of ontology are exploited in different parts of the retrieval cycle including query-based relevance measures, semantic user preference representation and automatic update, and personalized result ranking. Both the usage and information resources can be exploited to extract useful knowledge from the way users interact with a digital library. Through combination and mapping between the extracted knowledge and domain ontology, semantic content retrieval between queries and documents can be utilized. Furthermore, ontology-based conceptual vector of user preference can be applied in personalized recommendation feedback.展开更多
A new(γA,σB)-matrix KP hierarchy with two time series γA and σB,which consists of γA-flow,σB-flow and mixed γA and σB-evolution equations of eigenfunctions,is proposed.The reduction and constrained flows of(...A new(γA,σB)-matrix KP hierarchy with two time series γA and σB,which consists of γA-flow,σB-flow and mixed γA and σB-evolution equations of eigenfunctions,is proposed.The reduction and constrained flows of(γA,σB)matrix KP hierarchy are studied.The dressing method is generalized to the(γA,σB)-matrix KP hierarchy and some solutions are presented.展开更多
基金The Young Teachers Scientific Research Foundation(YTSRF) of Nanjing University of Science and Technology in the Year of2005-2006.
文摘To promote information service ability of digital libraries, a browsing and searching personalized recommendation framework based on the use of ontology is described, where the advantages of ontology are exploited in different parts of the retrieval cycle including query-based relevance measures, semantic user preference representation and automatic update, and personalized result ranking. Both the usage and information resources can be exploited to extract useful knowledge from the way users interact with a digital library. Through combination and mapping between the extracted knowledge and domain ontology, semantic content retrieval between queries and documents can be utilized. Furthermore, ontology-based conceptual vector of user preference can be applied in personalized recommendation feedback.
基金Supported by the National Science Foundation of China under Grant Nos. 10801083,10901090,11171175China Postdoctoral Science Funded Project (20110490408)Chinese Universities Scientific Fund under Grant No. 2011JS041
文摘A new(γA,σB)-matrix KP hierarchy with two time series γA and σB,which consists of γA-flow,σB-flow and mixed γA and σB-evolution equations of eigenfunctions,is proposed.The reduction and constrained flows of(γA,σB)matrix KP hierarchy are studied.The dressing method is generalized to the(γA,σB)-matrix KP hierarchy and some solutions are presented.
