Intelligent Semantic Web Research Articles

OntoCommerce: an ontology focused semantic framework for personalised product recommendation for user targeted e-commerce

With the paradigm shift in business strategy in terms of online marketing and e-commerce and to comprehend the World Wide Web transforming into an intelligent semantic web, there arises a perpetual need for semantically driven e-commerce systems which gives preference to the users. In this paper, OntoCommerce which is an e-commerce system that incorporates semantic algorithms for product recommendation has been proposed. The proposed strategy uses the enriched normalised pointwise mutual information measure for semantic similarity computation. OntoCommerce assimilates ontologies and recommends products based on the user query, recorded user navigation as well as the user profile analysis thereby encompassing personalisation. In order to make the recommendations more relevant, OntoCommerce uses parametric fuzzification to increase the number of relevant recommendable products. OntoCommerce yields an average accuracy of 88.68 % with a low false discovery rate of 0.13 which makes it a best-in-class semantically driven product recommendation system for online e-commerce.

Survey on Intelligent Semantic Web Search Engines as Generic Search Engine

From the large database repositories globally the World Wide Web (WWW) allows the people to share the information (data). Billions of databases grown by the amount of information. We need to search the information will specialize tools known generically search engine. Many search engines available today for retrieving meaningful information is difficult. However to overcome this problem in search engines to retrieve meaningful information intelligently, semantic web technologies are playing a major role. In this paper we present survey on the search engine generations and the role of search engines in intelligent web and semantic search technologies.

Googling for Health Information

Googling for Health Information

Applying intelligent agents and semantic web services in eGovernment environments

The increasing volume of eGovernment-related services is demanding new approaches for service integration and interoperability in this domain. Semantic web (SW) technologies and applications can leverage the potential of eGovernment service integration and discovery, thus tackling the problems of semantic heterogeneity characterizing eGovernment information sources and the different levels of interoperability. eGovernment services will therefore be semantically described in the foreseeable future. In an environment with semantically annotated services, software agents are essential as the entities responsible for exploiting the semantic content in order to automate some tasks, and so enhance the user's experience. In this paper, we present a framework that provides a seamless integration of semantic web services and intelligent agents technologies by making use of ontologies to facilitate their interoperation. The proposed framework can assist in the development of powerful and flexible distributed systems in complex, dynamic, heterogeneous, unpredictable and open environments. Our approach is backed up by a proof-of-concept implementation, where the breakthrough of integrating disparate eGovernment services has been tested.

Non-Monotonic Modeling for Personalized Services Retrieval and Selection

With growing interest in Semantic Web services and emerging standards, such as OWL, WSMO, and SWSL in particular, the importance of applying logic-based models to develop core elements of the intelligent Semantic Web has been more closely examined. However, little research has been conducted in Semantic Web services on issues of non-mono-tonicity and uncertainty of Web services retrieval and selection. In this paper, the authors propose a non-monotonic modeling and uncertainty reasoning framework to address problems related to adaptive and personalized services retrieval and selection in the context of micro-payment processing of electronic commerce. As intelligent payment service agents are faced with uncertain and incomplete service information available on the Internet, non-monotonic modeling and reasoning provides a robust and powerful framework to enable agents to make service-related decisions quickly and effectively with reference to an electronic payment processing cycle.

EManaging Ambient Organizations in 3D

As we work in different constellations, levels, networks, and sub networks etc., we need to see networking in multiple dimensions, i.e. as ambient organizations. To summarize the problem statement the article is addressing whether or not there is an added value for interpreting the structure of collaboration by managing ambient organizations in 3D. By utilizing a cybernetic structure and combining a set of specific methods, a clear separation between narrative, content, and contexts of organizations can be determined and challenge the old traditional way of scientific and knowledge management. Take Stafford Beer's methodology of Team Syntegrity which is based on cybernetic system theory where he uses the model of regular polyedra's to manage knowledge creating and transferring by organizing individuals with a strict cybernetic structure, and see the group of individuals re-arrange themselves in a self-organizing way. This three dimensional approach of eManagement is used as a platform for suggestions of more 3D tools communication, knowledge-sharing and innovation through the use of the theory on Information Space by Max Boisot. This article focuses upon an ICT and organizational approach to show the difficulties in creating a network based on a virtual platform without equal contribution and interest by all parties involved and a common vision that motivate the individuals to be a part of the network. The support of this multi-dimensionality from information and communication technologies (ICT) moves us towards using the dynamics of social technologies as Web 2.0 (ff Web 3.0) and an intelligent semantic web. Both the ambient organization and the social technologies available raise the challenge of changing our mindset in order to be able to manage at all. Finally the paper applies these systems on the challenge of asymmetric information, globalization, and the economics at the bottom of the pyramid (BOP), which could be implemented or visualized as an e-business model.

A New Framework for Intelligent Semantic Web Services Based on GAIVAs

The Semantic Web has been recently developed to provide end users with suitable tools and strategies to process information from their Web pages. The Intelligent Semantic Web Services is a new approach aimed at extending Semantic Web capabilities for Services by applying Artificial Intelligence techniques while maintaining the good properties of the standard Semantic Web schemes. However, many current Web services neither consider this approach nor include a powerful user-interface and, consequently, are very limited and difficult to use. This paper introduces a new framework for Intelligent Semantic Web Services that overcomes these drawbacks. Our approach is based on the Graphical Autonomous Intelligent Virtual Agents (GAIVAs), virtual agents that exhibit a human-like appearance and behaviour and are able to take intelligent decisions and perform actions without human intervention. To this purpose, the framework comprises a collection of powerful Artificial Intelligence techniques along with a natural and intuitive Graphical User Interface.

Provision of semantic web services through an intelligent semantic web service finder

This paper shows a searching mechanism to discover Semantic Web Services satisfying client requirements. The increase in web services and lack of semantic base in search mechanisms of UDDI make it difficult for clients to find a required web service.

Combining weights with fuzziness for intelligent semantic web search

Intelligent retrieval for best satisfying users search intensions still remains a challenging problem due to the inherent complexity of real-world semantic web applications. Usually, a search request contains not only vagueness or imprecision, but also personalized information goals. This paper presents a novel approach which formulates one’s search request through tightly combining fuzziness together with the user’s subjective weighting importance over multiple search properties. A special ranking mechanism based on the weighed fuzzy query representation is proposed. The ranking method generates a set of “degree of relevance” – an overall score which reflects both fuzzy predicates and the user’s personalized preferences in the search request. Moreover, the ranking method is general and unique rather than arbitrary. Hence, search results shall be properly ordered in terms of their relevance with respect to best matching the search intension. The experimental results show that our approach can effectively capture users information goals and produce much better search results than existing approaches.