5757371
A Semantic Framework for Distributed Applications
19524119
Challenges and Opportunities for Web Services Research - Editorial Preface
34237375
On-Demand Business Collaboration Enablement with Services Computing
In this talk, I will introduce a model for on-demand business process based collaboration, namely, Extended Business Collaboration (eBC), and its major characteristics: modeling, solution stack, configurable business protocol enabling framework, on-demand services deployment, as well as monitoring and analytical control. Then we present a few major research issues associated with facilitating extended business collaboration, followed by our proposed Annotated Business HyperChain technology leveraging Services computing and semantic annotation model. Services computing is the evolution of Internet computing by leveraging services oriented architecture. Services computing is mainly targeting for a new ground break technology suite – Web services and services oriented Grid/Utility Computing, Business Computing, and Autonomic Computing. A research prototype is illustrated at the end of the talk followed by some observations and discussion of open research issues requiring further exploration.
32965761
The Next Big Thing: Web Services Collaboration
In this paper, we introduce the lifecycle of a Web services solution that consists of Web services modeling, development, deployment, publishing, as well as discovery, composition and collaboration, plus monitoring and analytical control. Then some research and development challenges of building a Web services solution in the context of Web services solution lifecycle are described. Especially, we present an emerging Web services research direction, namely, Web services collaboration, followed by a few major research issues associated with facilitating extended business collaboration using Web services and semantic annotation.
19467963
An integrated live interactive content insertion system for digital TV commerce
We present an advanced architecture for selectively inserting interactive content into a live TV broadcast anti tracking the usage of the inserted content by client viewers. Specifically, we propose a multi-level interactive content preview mechanism, agent-based information exchange mechanism and E-commerce enablement technology powered by an Interactive Content Creation Engine (ICCE). Also, we introduce two types of mapping lists for scheduling and for an intelligent decision maker based oil the transaction monitoring and multi-level content preview. We propose that the improved live interactive content insertion method and system will be especially useful for building interactive TV e-commerce solutions.
17426553
On-demand business collaboration enablement with web services
Businesses are increasingly outsourcing key operations and interacting with ever extending nets of partners. Running extended business-to-business (B2B) operations creates the need for more advanced human interaction while advancing the automation base of B2B functions. In this paper, we introduce a model for on-demand business process-based collaboration, namely, Extended Business Collaboration (eBC), and its major elements of modeling, and a configurable business protocol-enabling framework. We discuss some of the major research issues associated with facilitating extended business collaboration, and present our proposed Annotated Business HyperChain technology leveraging Web services and semantic annotation model. A research prototype is described, followed by some observations and discussion of open research issues requiring further exploration.
6538157
Threshold Tuning for Improved Classification Association Rule Mining
One application of Association Rule Mining (ARM) is to identify Classification Association Rules (CARs) that can be used to classify future instances from the same population as the data being mined. Most CARM methods first mine the data for candidate rules, then prune these using coverage analysis of the training data. In this paper we describe a CARM algorithm that avoids the need for coverage analysis, and a technique for tuning its threshold parameters to obtain more accurate classification. We present results to show this approach can achieve better accuracy than comparable alternatives at lower cost.
16393711
Salient Feature Selection for Visual Concept Learning
Image classification could be treated as an effective solution to enable keyword-based semantic image retrieval. In this paper, we propose a novel image classification framework by learning semantic concepts of image categories. To choose representative features for an image category and meanwhile reduce noisy features, a three-step salient feature selection strategy is proposed. In the feature selection stage, salient patches are first detected and clustered. Then the region of dominance and salient entropy measures are calculated to reduce non-common salient patches for the category. Based on the selected visual keywords, SVM and keyword frequency model categorization method are applied to classification, respectively. The experimental results on Corel image database demonstrate that the proposed salient feature selection approach is very effective in image classification and visual concept learning.
40461324
On the Classification of UML's Meta Model Extension Mechanism
Although the UML meta model extension mechanism has been used in many modeling fields in which extension of UML is needed, UML specification has little necessary classification and application guidance on the meta model extension mechanism. This paper defines four levels of UML’s meta model extension mechanism, and discusses the readability, expression capability, use scope and tool support on the basis of precise definitions of each level. The work on the paper reinforces the maneuverability of the UML meta model extension mechanism, and provides a reliable theoretical base for the development of modeling tools that support meta model extension.
8187115
Modeling location management in wireless networks with generally distributed parameters
In the wireless mobile networks, location update (LU) and paging are two basic operations in the framework of mobility management. The trade-off analysis between LU and paging is traditionally performed under the assumption that the key variables follow exponential distribution. However, recent work showed that such assumptions may be incorrect. In this paper, by introducing the concept of LU inter-arrival time and additionally relaxing the assumptions for the inter-service time, cell residence time and LU inter-arrival time, we present an analytical technique to develop the closed-form formula for the signaling cost applicable to different location management schemes. Specifically, the result is applied to the static scheme and the dynamic movement-based scheme to demonstrate the general applicability. Illustrative numerical examples are given to compare the location management scheme performance based on the cell characteristics.
214819
Scalable search-based image annotation of personal images
With the prevalence of digital cameras, more and more people have considerable digital images on their personal devices. As a result, there are increasing needs to effectively search these personal images. Automatic image annotation may serve the goal, for the annotated keywords could facilitate the search processes. Although many image annotation methods have been proposed in recent years, their effectiveness on arbitrary personal images is constrained by their limited scalability, i.e. limited lexicon of small-scale training set. To be scalable, we propose a search-based image annotation (SBIA) algorithm that is analogous to Web page search. First, content-based image retrieval (CBIR) technology is used to retrieve a set of visually similar images from a large-scale Web image set. Then, a text-based keyword search (TBKS) technique is used to obtain a ranked list of candidate annotations for each retrieved image. Finally, a fusion algorithm is used to combine the ranked lists into the final annotation list. The application of both efficient search technologies and Web-scale image set guarantees the scalability of the proposed algorithm. Experimental results on U. Washington dataset show not only the effectiveness and efficiency of the proposed algorithm but also the advantage of image retrieval using annotation results over that using visual features.