13388104
MetaData Pro: Ontology-Based Metadata Processing for Web Resources
Metadata is the foundation of Semantic Web. The MetaData Pro project seeks to build a metadata processing platform for web resource. The system architecture has three key components– Metadata Extraction, Ontology Management, and Metadata Retrieval. The system can automatically extract metadata about web resource: if the web resource itself contains metadata, extracts them; otherwise, automatically generates the metadata for the resource according to Dublin Core by applying automatic keyword extraction and text summarization techniques. To manage the metadata, MetaData Pro integrates Protege to create domain ontology, makes use of HowNet to help ontology construction, and provides an ontology-based metadata retrieval.
37473996
Representing Wholes by Structure
The influence of Part-Whole relationship (partof) on ontology languages is weak because the special semantics of partof is missed in both representations and interpretations. In this paper, we first exemplify the complexity and limitation of using partof for representing wholes. We then investigate the special semantics of partof by analyzing the properties of parts and wholes. The conclusion is that a part should be regarded as something internal to certain whole and a whole is a structured thing which is comprised of some internal things. The special semantics are achieved by introducing some new constructs which are whole structure, part type, role type, Ontology, defined-in relation and play relation. Because the whole structure possesses inherent modularity and local semantics, the representation is very natural and simple. We show the generality and applicability of the presented approach in terms of the problems pointed out in the paper.
9457575
Secure Mobile Code Execution Service
Mobile code refers to programs that come into a host computer over the network and start to execute with or without a user's knowledge or consent. Because these programs run in the execution context of the user that downloads them, they can issue any system calls that the user is allowed to make, and thus pose a serious security threat when they are malicious. Although many solutions have been proposed to solve the malicious mobile code problem, none of them are truly effective at striking a good balance between defeating zero-day attacks and minimizing disruption to the execution of legitimate applications. 
 
This paper describes a commercial system called SEES that secures the execution of mobile code that comes into a host computer as an email attachment or as a web document downloaded through an anchor link by running them on a separate guinea pig machine rather than on the user machine. Effectively, it takes an isolation approach to the secure mobile code execution problem. As a result, SEES guarantees that no malicious email attachments or web documents that act on behalf of the user that downloads them, can damage the resources of the user machine, or can leak any confidential information. In particular, even zero-day virus cannot cause any harms. We present the design, implementation and evaluation of SEES on the Windows platform, and contrast it with other existing approaches to the same problem.
12506111
A Case Study in Integrating Multiple E-commerce Standards via Semantic Web Technology
Internet business-to-business transactions present great challenges in merging information from different sources. In this paper we describe a project to integrate four representative commercial classification systems with the Federal Cataloging System (FCS). The FCS is used by the US Defense Logistics Agency to name, describe and classify all items under inventory control by the DoD. Our approach uses the ECCMA Open Technical Dictionary (eOTD) as a common vocabulary to accommodate all different classifications. We create a semantic bridging ontology between each classification and the eOTD to describe their logical relationships in OWL DL. The essential idea is that since each classification has formal definitions in a common vocabulary, we can use subsumption to automatically integrate them, thus mitigating the need for pairwise mappings. Furthermore our system provides an interactive interface to let users choose and browse the results and more importantly it can translate catalogs that commit to these classifications using compiled mapping results.
14798479
Learning the Semantic Meaning of a Concept from the Web
Many researchers have used text classification method in solving the ontology mapping problem. Their mapping results heavily depend on the availability of quality exemplars used as training data. However, manual preparation of exemplars is costly. In this work, we propose to automatically extract text from web pages returned by a search engine. Search queries are formed according to the semantic information given in the ontology. We have implemented a prototype system that automates the entire process (from search query formation to conditional probability calculation) and conducted a series of experiments. We assessed the effectiveness of our approach by comparing the obtained conditional probabilities with human expectations. Our main contribution is that we explored the possibilities of utilizing web information for text classification based ontology mapping and made several valuable discoveries on its usefulness for future research.
6083994
On communication models for algorithm design in networked sensor systems: A case study,
Towards building a systematic methodology of algorithm design for applications of networked sensor systems, we formally define two link-wise communication models, the Collision Free Model (CFM) and the Collision Aware Model (CAM). While CFM provides ease of programming and analysis for high level application functionality, CAM enables more accurate performance analysis and hence more efficient algorithms through cross-layer optimization, at the expense of increased programming and analysis complexity. These communication models are part of an abstract network model, above which algorithm design and performance optimization is performed. We use the example of optimizing a probability based broadcasting scheme under CAM to illustrate algorithm optimization based on the defined models. Specifically, we present an analytical framework that facilitates an accurate modeling and analysis for the probability based broadcasting in CAM (PB_CAM). Our analytical results indicate that (1) the optimal broadcast probability for either maximizing the reachability within a given latency constraint or minimizing the latency for a given reachability constraint decreases rapidly with node density, and (2) the optimal probability for either maximizing the reachability with a given energy constraint or minimizing the energy cost for a given reachability constraint varies slowly between 0 and 0.1 over the entire range of the variations in node density. Our analysis is also confirmed by extensive simulation results.
723568
A Bayesian Network Approach to Ontology Mapping
This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web. In this approach, the source and target ontologies are first translated into Bayesian networks (BN); the concept mapping between the two ontologies are treated as evidential reasoning between the two translated BNs. Probabilities needed for constructing conditional probability tables (CPT) during translation and for measuring semantic similarity during mapping are learned using text classification techniques where each concept in an ontology is associated with a set of semantically relevant text documents, which are obtained by ontology guided web mining. The basic ideas of this approach are validated by positive results from computer experiments on two small real-world ontologies.