PGSW-OS: a novel approach for resource management in a semantic web operating system based on a P2P grid architecture

A web operating system is an operating system that users can access from any hardware at any location. A peer-to-peer (P2P) grid uses P2P communication for resource management and communication between nodes in a grid and manages resources locally in each cluster, and this provides a proper architecture for a web operating system. Use of semantic technology in web operating systems is an emerging field that improves the management and discovery of resources and services. In this paper, we propose PGSW-OS (P2P grid semantic Web OS), a model based on a P2P grid architecture and semantic technology to improve resource management in a web operating system through resource discovery with the aid of semantic features. Our approach integrates distributed hash tables (DHTs) and semantic overlay networks to enable semantic-based resource management by advertising resources in the DHT based upon their annotations to enable semantic-based resource matchmaking. Our model includes ontologies and virtual organizations. Our technique decreases the computational complexity of searching in a web operating system environment. We perform a simulation study using the Gridsim simulator, and our experiments show that our model provides enhanced utilization of resources, better search expressiveness, scalability, and precision. © 2014 Springer Science+Business Media New York.

Threshold concepts and the semantic web

Threshold concepts have proven to be a useful tool in understanding a particular set of difficulties that confront students in higher education. From the viewpoint of a student threshold concepts are characterized as transformative, integrative, bounded, troublesome, and to a large extent invisible. The sematic web, among its many other advantages, holds the possibility of allowing students to successfully move beyond the threshold concepts in their chosen discipline. The nature of threshold concepts are discussed and related specifically to andragogy. A preliminary solution, which takes advantage of the features of Web 3.0, is presented.

Semantic Web for the legal domain: the next step

Ontology-driven systems with reasoning capabilities in the legal field are now better understood. Legal concepts are not discrete, but make up a dynamic continuum between common sense terms, specific technical use, and professional knowledge, in an evolving institutional reality. Thus, the tension between a plural understanding of regulations and a more general understanding of law is bringing into view a new landscape in which general legal frameworks – grounded in well-known legal theories stemming from 20th-century c. legal positivism or sociological jurisprudence – are made compatible with specific forms of rights management on the Web. In this sense, Semantic Web tools are not only being designed for information retrieval, classification, clustering, and knowledge management. They can also be understood as regulatory tools, i.e. as components of the contemporary legal architecture, to be used by multiple stakeholders – front-line practitioners, policymakers, legal drafters, companies, market agents, and citizens. That is the issue broadly addressed in this Special Issue on the Semantic Web for the Legal Domain, overviewing the work carried out over the last fifteen years, and seeking to foster new research in this field, beyond the state of the art.

A smart web service based on the context of things

Combining the Semantic Web and the Ubiquitous Web, Web 3.0 is for things. The Semantic Web enables human knowledge to be machine-readable and the Ubiquitous Web allows Web services to serve any thing, forming a bridge between the virtual world and the real world. By using context, Web services can become smarter-that is, aware of the target things' or applications' physical environments, or situations and respond proactively and intelligently. Existing methods for implementing context-aware Web services on Web 2.0 mainly enumerate different implementations corresponding to different attribute values of the context, in order to improve the Quality of Services (QoS). However, things in the physical world are extremely diverse, which poses new problems for Web services: it is difficult to unify the context of things and to implement a flexible smart Web service for things. This article proposes a novel smart Web service based on the context of things, which is implemented using a REpresentational State Transfer for Things (Thing-REST) style, to tackle the two problems. In a smart Web service, the user's description (semantic context) and sensor reports (sensing context) are two channels for acquiring the context of things which are then employed by ontology services to make the context of things machine-readable. With guidance of domain knowledge services, event detection services can analyze things' needs particularly, well through the context of things. We then propose a Thing-REST style to manage the context of things and user context, and to mashup Web services through three structures (i.e., chain, select, and merge) to implement smart Web services. A smart plant watering-service application demonstrates the effectiveness of our method. © 2012 ACM.

Ontology learning from text: a soft computing paradigm

Text-based information accounts for more than 80% of today’s Web content. They consist of Web pages written in different natural languages. As the semantic Web aims at turning the current Web into a machine-understandable knowledge repository, availability of multilingual ontology thus becomes an issue at the core of a multilingual semantic Web. However, multilingual ontology is too complex and resource intensive to be constructed manually. In this paper, we propose a three-layer model built on top of a soft computing framework to automatically acquire a multilingual ontology from domain specific parallel texts. The objective is to enable semantic smart information access regardless of language over the Semantic Web.

The development of a wisdom autonomic grid

It is not a simple matter to develop an integrative approach that exploits  synergies between knowledge management and knowledge discovery in   order to monitor and manage the full lifecycle of knowledge and provides  services quickly, reliably and securely. One of the main problems is the heterogeneity of the involved resources that represent knowledge. Data mining systems produce knowledge in a form meant to be understandable  to machines and on the other hand in knowledge management systems the  priority is placed on the readability and usability of knowledge by humans.  The Semantic Web is a promising platform to unify this heterogeneity and, in conjunction with novel techniques for Web Intelligence it could offer more  then just knowledge - wisdom. The Wisdom Autonomic Grid is an original proposal of a knowledge based Grid that is able to configure and reconfigure itself under varying and unpredictable conditions and optimize its working, performs something akin to healing and provides self-protection, as  visioned in the IBM Autonomic Computing initiative. This paper presents an original framework for creating advanced applications to integrate  knowledge discovery and knowledge management in the Autonomic Grid  and Web environments.

Algorithm for web services matching

UDDI is a standard for publishing and discovery of web services. UDDI registries provide keyword searches for web services. The search functionality is very simple and fails to account for relationships between web services. In this paper, we propose an algorithm which retrieves closely related web services. The proposed algorithm is based on singular value decomposition (SVD) in linear algebra, which reveals semantic relationships among web services. The preliminary evaluation shows the effectiveness and feasibility of the algorithm.

Mining more gold from web page hyperlinks

The development of the Internet has boosted prosperity of the World Wide Web, which is now a huge information source. Because of characteristics of the web, in most cases, traditional databasebased technologies are no longer suitable for web information retrieval and management. To effectively manage web information, it is necessary to reveal intrinsic relationships/structures among web information objects by eliminating noise factors. This paper proposes a mechanism that could be widely used in information processing, including web information processing and noise factor elimination for getting more intrinsic relationships. As an application case of this mechanism, one relevant web page finding algorithm is proposed to uncover intrinsic relationship among web pages from their hyperlink patterns, and find more semantic relevant web pages. The experimental evaluation shows the feasibility and effectiveness of the algorithm and demonstrates the potential of the proposed mechanism in web applications.

Fuzzy-neuro web-based multilingual knowledge management

This paper presents new methodology towards the automatic development of multilingual Web portal for multilingual knowledge discovery and management. It aims to provide an efficient and effective framework for selecting and organizing knowledge from voluminous linguistically diverse Web contents. To achieve this, a concept-based approach that incorporates text mining and Web content mining using neural network and fuzzy techniques is proposed. First, a concept-based taxonomy of themes, which will act as the hierarchical backbone of the Web portal, is automatically generated. Second, a concept-based multilingual Web crawler is developed to intelligently harvest relevant multilingual documents from the Web. Finally, a concept-based multilingual text categorization technique is proposed to organize multilingual documents by concepts. As such, correlated multilingual Web documents can be gathered/filtered/organised/ based on their semantic content to facilitate high-performance multilingual information access.

Discovering Web Page Communities

The rapid development of Web technologies has made the World Wide Web a huge information source. However, due to the lack of a well-defined underlying data model for Web documents, effectively and efficiently finding required information and managing Web data are usually tedious and difficult tasks when using conventional information retrieval and data management techniques. The Web page community, defined as a set of Web-based documents with its own logical and/or semantic structures, provides a flexible and effective approach to support Wed data management, information retrieval and applications. This book addresses using hyperlink information to discover Web page communities. The work establishes a uniform framework for hyperlink analysis and community construction. Algorithms, supporting mechanisms and data models are proposed in the book. This book should help shed some light on this new and exciting research and application area. It is useful to researchers and students in Web mining, Web data management and information retrieval, as well as to professionals who may be considering utilizing Web communities to improve their applications.

CARSA : A context-aware reasoning-based service agent model for AI planning of web service compostion

In order to achieve automatic and more intelligent service composition, dynamic description logic (DDL) is proposed and utilized as one emerging logic-level solution. However, reasoning optimization and utilization in such DDL-related solutions is still an open problem. In this paper, we propose the context-aware reasoning-based service agent model (CARSA) which exploits the relationships among different service consumers and providers, together with the corresponding optimization approach to strengthen the effectiveness of Web service composition. Through the model, two reasoning optimization methods are proposed based on the substitute relationship and the dependency relationship, respectively, so irrelevant actions can be filtered out of the reasoning space before the DDL reasoning process is carried out. The case study and experimental analysis demonstrates the capability of the proposed approach.

Web services for things

In this chapter, we introduce an interesting type of Web services for "things". Existing Web services are applications across the Web that perform functions mainly to satisfy users' social needs "from simple requests to complicated business processes". Throughout history, humans have accumulated lots of knowledge about diverse things in the physical world. However, human knowledge about the world has not been fully used on the current Web which focuses on social communication; the prospect of interacting with things other than people on the future Web is very exciting. The purpose of Web services for "things" is to provide a tunnel for people to interact with things in the physical world from anywhere through the Internet. Extending the service targets from people to anything challenges the existing techniques of Web services from three aspects: first, an unified interface should be provided for people to describe the needs of things; then basic components should be designed in a Web service for things; finally, implementation of a Web service for things should be optimized when mashing up multiple sub Web services. We tackle the challenges faced by a Web service for things and make the best use of human knowledge from the following aspects. We first define a context of things as an unified interface. The users' description (semantic context) and sensors (sensing context) are two channels for acquiring the context of things. Then, we define three basic modules for a Web service for things: ontology Web services to unify the context of things, machine readable domain knowledge Web services and event report Web services (such as weather report services and sensor event report services). Meanwhile, we develop a Thing-REST framework to optimally mashup structures to loosely couple the three basic modules. We employ a smart plant watering service application to demonstrate all the techniques we have developed.