Context aware guidance for multimedia authoring: harmonizing domain and discourse knowledge

This paper presents an approach to assist authors during the authoring of multimedia presentations. We extend the existing authoring support by integrating processes of topic identification, content collection and discourse structure building in a single environment. This integration allows identification of the context of the authoring process. Our approach combines this process context awareness with explicit domain and discourse knowledge to steer system suggestions. We evaluate our approach with an experimental system prototype.     

Putting Web Services in Context

When considering the full range of Web service-related activities, it becomes clear that dealing with context is a major challenge, requiring greater expressiveness, reasoning capabilities, and architectural components than are provided by the current widely accepted building blocks of the Web services stack. This paper presents an informal overview of concepts, requirements and challenges for handling contextual knowledge in connection with Web services, and briefly discusses several interesting projects in this area of research.     

Efficient data selection for speech recognition based on prior confidence estimation using speech and monophone models

This paper proposes an efficient speech data selection technique that can identify those data that will be well recognized. Conventional confidence measure techniques can also identify well-recognized speech data. However, those techniques require a lot of computation time for speech recognition processing to estimate confidence scores. Speech data with low confidence should not go through the time-consuming recognition process since they will yield erroneous spoken documents that will eventually be rejected. The proposed technique can select the speech data that will be acceptable for speech recognition applications. It rapidly selects speech data with high prior confidence based on acoustic likelihood values and using only speech and monophone models. Experiments show that the proposed confidence estimation technique is over 50 times faster than the conventional posterior confidence measure while providing equivalent data selection performance for speech recognition and spoken document retrieval.     

A formal representation for context-aware business processes

A business process is a set of activities performed in a coordinated manner within an organizational and technical environment that is aimed toward a business goal. The flexibility of a process is related to an understanding of the unexpected events that occur when people, systems and resources interact and require adjustments. Thus, business processes must be designed to respond to information about different events and their specificity. This information defines what the literature calls “context”. To broaden the perception of context in the case of a business process, this work proposes an approach to characterize the context of a business process activity in a given domain through conceptual models structured in layers. A case study was conducted to evaluate the proposal, which provided evidence of the applicability of the model.     

一种基于上下文的医学图像ROI分类方法

感兴趣区域(ROI)的分类是医学图像的计算机辅助诊断过程的最后一步,传统方法只针对每个ROI区域单独提取特征,再利用统计学习的方法训练分类器进行分类.然而图像中每个区域所包含的视觉特征有限,很难进行准确的分类.文中提出一种基于LDA主题模型的改进模型(LDAC),考虑ROI周围区域,即图像的上下文关系,通过利用LDA对ROI周围区域所包含的上下文信息进行建模,同时结合ROI区域的视觉信息和类别标签,从而辅助ROI区域的分类,以达到提高分类准确率的目的.乳腺图像肿块分类实验表明,文中方法可提高分类的准确性.     

Towards a trust,reputation and recommendation meta model

New trust, reputation and recommendation (TRR) models are continuously proposed. However, the existing models lack shared bases and goals. For this reason, in this work we define an innovative meta model to facilitate the definition and standardization of a generic TRR model. Following the meta model, researchers in the field will be able to define standard models, compare them with other models and reuse parts of them. A standardization is also needed to determine which properties should be present in a TRR model.In accordance with the objectives we were seeking, following our meta model, we have defined a pre-standardized TRR model for e-commerce, identified the fundamental concepts and the main features that contribute to form trust and reputation in that domain, respected the dependence on the context/role of trust and reputation, aggregated only homogeneous trust information; listed and shown how to defend from the main malicious attacks.     

基于GLR算法的维吾尔语句法分析研究

采用GLR算法对维吾尔语句子进行句法分析,并且与平行LR算法进行比较,比较它们的分析过程,针对于维吾尔语在单词集上进行句法分析。分析结果采用最优规则,选取最优的句法分析树,对下一步的句法分析研究提供很大的帮助。     

试谈Tcl的闭包

为在Tcl编程语言中加入闭包（匿名函数）,先对Tcl和闭包进行必要的了解,结合两者的特点,提出了针对Tcl的闭包解决方案,通过在闭包代码段前增加上下文环境信息以及组成,以列表参数和代码段为基础的闭包结构,成功地模拟出了闭包这一编程特性,给简化Tcl代码和优化Tcl代码结构提供了一个简单而高效的工具。     

Learning to learn: From smart machines to intelligent machines

Since its birth, more than five decades ago, one of the biggest challenges of artificial intelligence remained the building of intelligent machines. Despite amazing advancements, we are still far from having machines that reach human intelligence level. The current paper tries to offer a possible explanation of this situation. For this purpose, we make a review of different learning strategies and context types that are involved in the learning process. We also present the results of a study on cognitive development applied to the problem of face recognition for social robotics.