35,182 research outputs found
Layered evaluation of interactive adaptive systems : framework and formative methods
Peer reviewedPostprin
A Dynamic Knowledge Management Framework for the High Value Manufacturing Industry
Dynamic Knowledge Management (KM) is a combination of cultural and technological factors, including the cultural factors of people and their motivations, technological factors of content and infrastructure and, where these both come together, interface factors. In this paper a Dynamic KM framework is described in the context of employees being motivated to create profit for their company through product development in high value manufacturing. It is reported how the framework was discussed during a meeting of the collaborating company’s (BAE Systems) project stakeholders. Participants agreed the framework would have most benefit at the start of the product lifecycle before key decisions were made. The framework has been designed to support organisational learning and to reward employees that improve the position of the company in the market place
CASP-DM: Context Aware Standard Process for Data Mining
We propose an extension of the Cross Industry Standard Process for Data
Mining (CRISPDM) which addresses specific challenges of machine learning and
data mining for context and model reuse handling. This new general
context-aware process model is mapped with CRISP-DM reference model proposing
some new or enhanced outputs
OpenPING: A Reflective Middleware for the Construction of Adaptive Networked Game Applications
The emergence of distributed Virtual Reality (VR) applications
that run over the Internet has presented networked game
application designers with new challenges. In an environment
where the public internet streams multimedia data and is
constantly under pressure to deliver over widely heterogeneous
user-platforms, there has been a growing need that distributed VR
applications be aware of and adapt to frequent variations in their
context of execution. In this paper, we argue that in contrast to
research efforts targeted at improvement of scalability, persistence
and responsiveness capabilities, much less attempts have been
aimed at addressing the flexibility, maintainability and
extensibility requirements in contemporary distributed VR
platforms. We propose the use of structural reflection as an
approach that not only addresses these requirements but also
offers added value in the form of providing a framework for
scalability, persistence and responsiveness that is itself flexible,
maintainable and extensible. We also present an adaptive
middleware platform implementation called OpenPING1 that
supports our proposal in addressing these requirements
Understanding the relevance of national culture in international business research: a quantitative analysis
This review is a comprehensive quantitative analysis of the International Business literature whose focus is on national culture. The analysis relies on a broad range of bibliometric techniques as productivity rankings, citation analysis (individual and cumulative), study of collaborative research patterns, and analysis of the knowledge base. It provides insights on (I) faculty and institutional research productivity and performance; (II) articles, institutions, and scholars’ influence in the contents of the field and its research agenda; and (III) national and international collaborative research trends. The study also explores the body of literature that has exerted the greatest impact on the researched set of selected articles.info:eu-repo/semantics/publishedVersio
Classifying Web Exploits with Topic Modeling
This short empirical paper investigates how well topic modeling and database
meta-data characteristics can classify web and other proof-of-concept (PoC)
exploits for publicly disclosed software vulnerabilities. By using a dataset
comprised of over 36 thousand PoC exploits, near a 0.9 accuracy rate is
obtained in the empirical experiment. Text mining and topic modeling are a
significant boost factor behind this classification performance. In addition to
these empirical results, the paper contributes to the research tradition of
enhancing software vulnerability information with text mining, providing also a
few scholarly observations about the potential for semi-automatic
classification of exploits in the existing tracking infrastructures.Comment: Proceedings of the 2017 28th International Workshop on Database and
Expert Systems Applications (DEXA).
http://ieeexplore.ieee.org/abstract/document/8049693
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