Akira Kinno

Environment adaptive XML transformation and its application to content delivery

We propose a generic and computationally efficient framework within which input XML data can be transformed depending on environment descriptions (e.g., terminal capabilities) and rule descriptions (e.g., access policies). We adopt a hybrid approach; the transformation engine consists of XSLT and DOM processors. The input XML data is transformed by an XSLT instance that is adapted by a DOM programming whose inputs are environment descriptions and rule descriptions. We cache the XSLT instance for reuse. Suppose the number of environment descriptions is limited Since XSLT instances are produced for corresponding environment descriptions, new XSLT instances are not necessarily created for every input. Caching the XSLT instances and reducing the number of XSLT instances created yields significant computational advantage in large-scale multimedia content delivery. We will use the proposed framework for an AAA system of the multimedia content delivery and its network control.

An efficient caching mechanism for XML content adaptation

We propose an efficient caching mechanism for XML content adaptation. Our adaptation framework consists of two modules. One module generates transformation rules and the other transforms source XML contents using the transformation rules. Unlike conventional caching mechanisms that store transformed contents, our mechanism stores the transformation rules between two modules. We show its performance improvement in terms of measured hit ratio and space efficiency in a comparison with conventional mechanisms.

Web user profiling on proxy logs and its evaluation in personalization

We propose a web user profiling and clustering framework based on LDA-based topic modeling with an analogy to document analysis in which documents and words represent users and their actions. The main technical challenge addressed here is how to symbolize web access actions, by words, that are monitored through a web proxy. We develop a hierarchical URL dictionary generated from Yahoo! Directory and a cross-hierarchical matching method that provides the function of automatic abstraction. We apply the proposed framework to 7500 students in Osaka University. The framework is used to analyze their 40GB click streams over a 4 month period. We evaluate clustering-based recommendation effectiveness to confirm the optimality of the framework. The results show high hit precision compared with existing methods.

Topic analysis of web user behavior using LDA model on proxy logs

We propose a web user profiling and clustering framework based on LDA-based topic modeling with an analogy to document analysis in which documents and words represent users and their actions. The main technical challenge addressed here is how to symbolize web access actions, by words, that are monitored through a web proxy. We develop a hierarchical URL dictionary generated from Yahoo! Directory and a cross-hierarchical matching method that provides the function of automatic abstraction. We apply the proposed framework to 7500 students in Osaka University. The results include, for example, 24 topics such as Technology Oriented, Job Hunting, and SNS-addict. The results reflect the typical interest profiles of University students, while perplexity analysis is employed to confirm the optimality of the framework.

Environmentally-adaptive XML transformation and its application to content delivery

Environmentally-adaptive XML transformation is a key goal for content adaptation. It needs a standard and computationally efficient framework for transformation engine that can transform input XML data depending on environment descriptions (e.g. terminal capabilities) and rule descriptions (e.g. access policies). We propose a method to realize the framework. We adopt XSLT and DOM processors: the DOM processors use environment descriptions and rule descriptions in composing XLST instances; the XLST processors refer to the XLST instances in transforming the input XML data. We cache the XLST instances for reuse. Since one XLST instance is produced for each environment description, their number is manageable; XLST instances are not necessarily created for every input. Caching the XLST instances and reducing the number of XLST instances created yields a significant computational advantage in large-scale multimedia content delivery. We will use the proposed framework to create an AAA (authentication, authorization, and accounting) system for multimedia content delivery and network control.

Recursive application of structural templates to efficiently compress parsed XML

This paper proposes an efficient compression method for parsed XML. Our method involves structure-based compression (SBC). In contrast to SBC, our method recursively inputs compressed parsed XML by parsing template instances as a node. Simulation results show that our method can reduce the memory requirements for real XML contents by almost 18%, and retains its compression efficiency even if the application domain changes, while that of SBC varies depending on the structural templates provided. One application of our method is to accelerate the response to native XML database queries.