Combining Ontology with Intelligent Agent to Provide Negotiation Service

Author(s):  
Qiumei Pu ◽  
Yongcun Cao ◽  
Xiuqin Pan ◽  
Siyao Fu ◽  
Zengguang Hou

Agent and Ontology are distinct technologies that arose independent of each other, having their own standards and specifications. The semantics web is one of the popular research areas these days, and is based on the current Web, which adds more semantics to it for the purpose of building the Ontology of Web content. In this regard, application program on Web can make the purpose of cross-platform calculation come true by taking advantage of Ontology. However, agent is a theory able to enhance abstraction of software itself, and as it is know, negotiation protocol is the basic principle in the electronic commerce which has a direct impact on the efficiency of the negotiation. This study examines the communication architecture with negotiation protocol on the Semantic Web. Precisely speaking, agents make computing with Ontology, and the authors define an agent’s communication ontology for this communication framework and semantic web use Ontology to describe the negotiation protocol. In this context, the buyer or seller will be able to improve semantic cognitive in process of negotiation. Also, it can provide an intelligent platform for the information exchange on the same understanding about the content of communication in the electronic negotiation service.

Author(s):  
Qiumei Pu ◽  
Yongcun Cao ◽  
Xiuqin Pan ◽  
Siyao Fu ◽  
Zengguang Hou

Agent and Ontology are distinct technologies that arose independent of each other, having their own standards and specifications. The semantics web is one of the popular research areas these days, and is based on the current Web, which adds more semantics to it for the purpose of building the Ontology of Web content. In this regard, application program on Web can make the purpose of cross-platform calculation come true by taking advantage of Ontology. However, agent is a theory able to enhance abstraction of software itself, and as it is know, negotiation protocol is the basic principle in the electronic commerce which has a direct impact on the efficiency of the negotiation. This study examines the communication architecture with negotiation protocol on the Semantic Web. Precisely speaking, agents make computing with Ontology, and the authors define an agent’s communication ontology for this communication framework and semantic web use Ontology to describe the negotiation protocol. In this context, the buyer or seller will be able to improve semantic cognitive in process of negotiation. Also, it can provide an intelligent platform for the information exchange on the same understanding about the content of communication in the electronic negotiation service.


Author(s):  
Krzysztof Juszczyszyn

The World Wide Web (WWW) is a global, ubiquitous, and fundamentally dynamic environment for information exchange and processing. By connecting vast numbers of individuals, the Web enables creation of virtual communities, and during the last 10 years, became a universal collaboration infrastructure. The so-called Semantic Web, a concept proposed by Tim Berners-Lee, is a new WWW architecture that enhances content with formal semantics (Berners-Lee, Hendler, & Lassila, 2001). Hence, the Web content is made suitable for machine processing (i.e., it is described by the associated metadata), as opposed to HTML documents available only for human consumption. Languages such as Resource Description Framework (RDF) and Ontology Web Language (OWL) along with well-known XML are used for description of Web resources. In other words, the Semantic Web is a vision of the future Web in which information is given explicit meaning. This will enable autonomous software agents to reason about Web content and produce intelligent responses to events (Staab, 2002). The ultimate goal of the next generation’s Web is to support the creation of virtual communities which will be composed of software agents and humans cooperating within the same environment. Sharing knowledge within such a community requires a shared conceptual vocabularies—ontologies, which represent the formal common agreement about the meaning of data (Gomez-Perez & Corcho, 2002). Artificial intelligence defines ontologies as explicit, formal specification of a shared conceptualization (Studer, Benjamins, & Fensel, 1998). In this case, a conceptualization stands for an abstract model of some concept from the real world; explicit means that the type of concept used is explicitly defined. Formal refers to the fact that an ontology should be machine readable; and finally shared means that ontology expresses knowledge that is accepted by all the subjects. In short, an ontology defines the terms used to describe and represent an area of knowledge. However, the shared ontologies must be first constructed by using information from many sources which may be of arbitrary quality. Thus, it is necessary to find a way to seamlessly combine the knowledge from many sources, maybe diverse and heterogeneous. The resultant ontologies enable virtual communities and teams to manage and exchange their knowledge. It should be noted, that the word ontology has been used to describe notions with different degrees of structure—from taxonomies (e.g., Yahoo hierarchy), metadata schemes (e.g., Dublin Core), to logical theories. The Semantic Web needs ontologies with a significant degree of structure. These should allow the specification of at least the following kinds of things: • Concepts (which identify the classes of things like cars or birds) from many domains of interest • The relationships that can exist among concepts • The properties (or attributes) those concepts may have


Author(s):  
Krzysztof Juszczyszyn

The World Wide Web (WWW) is a global, ubiquitous, and fundamentally dynamic environment for information exchange and processing. By connecting vast numbers of individuals, the Web enables creation of virtual communities, and during the last 10 years, became a universal collaboration infrastructure. The so-called Semantic Web, a concept proposed by Tim Berners-Lee, is a new WWW architecture that enhances content with formal semantics (Berners-Lee, Hendler, & Lassila, 2001). Hence, the Web content is made suitable for machine processing (i.e., it is described by the associated metadata), as opposed to HTML documents available only for human consumption. Languages such as Resource Description Framework (RDF) and Ontology Web Language (OWL) along with well-known XML are used for description of Web resources. In other words, the Semantic Web is a vision of the future Web in which information is given explicit meaning. This will enable autonomous software agents to reason about Web content and produce intelligent responses to events (Staab, 2002). The ultimate goal of the next generation’s Web is to support the creation of virtual communities which will be composed of software agents and humans cooperating within the same environment. Sharing knowledge within such a community requires a shared conceptual vocabularies—ontologies, which represent the formal common agreement about the meaning of data (Gomez-Perez & Corcho, 2002). Artificial intelligence defines ontologies as explicit, formal specification of a shared conceptualization (Studer, Benjamins, & Fensel, 1998). In this case, a conceptualization stands for an abstract model of some concept from the real world; explicit means that the type of concept used is explicitly defined. Formal refers to the fact that an ontology should be machine readable; and finally shared means that ontology expresses knowledge that is accepted by all the subjects. In short, an ontology defines the terms used to describe and represent an area of knowledge. However, the shared ontologies must be first constructed by using information from many sources which may be of arbitrary quality. Thus, it is necessary to find a way to seamlessly combine the knowledge from many sources, maybe diverse and heterogeneous. The resultant ontologies enable virtual communities and teams to manage and exchange their knowledge. It should be noted, that the word ontology has been used to describe notions with different degrees of structure—from taxonomies (e.g., Yahoo hierarchy), metadata schemes (e.g., Dublin Core), to logical theories. The Semantic Web needs ontologies with a significant degree of structure. These should allow the specification of at least the following kinds of things: • Concepts (which identify the classes of things like cars or birds) from many domains of interest • The relationships that can exist among concepts • The properties (or attributes) those concepts may have


2019 ◽  
Vol 15 (4) ◽  
pp. 41-56 ◽  
Author(s):  
Ibukun Tolulope Afolabi ◽  
Opeyemi Samuel Makinde ◽  
Olufunke Oyejoke Oladipupo

Currently, for content-based recommendations, semantic analysis of text from webpages seems to be a major problem. In this research, we present a semantic web content mining approach for recommender systems in online shopping. The methodology is based on two major phases. The first phase is the semantic preprocessing of textual data using the combination of a developed ontology and an existing ontology. The second phase uses the Naïve Bayes algorithm to make the recommendations. The output of the system is evaluated using precision, recall and f-measure. The results from the system showed that the semantic preprocessing improved the recommendation accuracy of the recommender system by 5.2% over the existing approach. Also, the developed system is able to provide a platform for content-based recommendation in online shopping. This system has an edge over the existing recommender approaches because it is able to analyze the textual contents of users feedback on a product in order to provide the necessary product recommendation.


2009 ◽  
Vol 36 (2) ◽  
pp. 3167-3187 ◽  
Author(s):  
Francisco García-Sánchez ◽  
Rafael Valencia-García ◽  
Rodrigo Martínez-Béjar ◽  
Jesualdo T. Fernández-Breis

Author(s):  
Andrew Iliadis ◽  
Wesley Stevens ◽  
Jean-Christophe Plantin ◽  
Amelia Acker ◽  
Huw Davies ◽  
...  

This panel focuses on the way that platforms have become key players in the representation of knowledge. Recently, there have been calls to combine infrastructure and platform-based frameworks to understand the nature of information exchange on the web through digital tools for knowledge sharing. The present panel builds and extends work on platform and infrastructure studies in what has been referred to as “knowledge as programmable object” (Plantin, et al., 2018), specifically focusing on how metadata and semantic information are shaped and exchanged in specific web contexts. As Bucher (2012; 2013) and Helmond (2015) show, data portability in the context of web platforms requires a certain level of semantic annotation. Semantic interoperability is the defining feature of so-called "Web 3.0"—traditionally referred to as the semantic web (Antoniou et al, 2012; Szeredi et al, 2014). Since its inception, the semantic web has privileged the status of metadata for providing the fine-grained levels of contextual expressivity needed for machine-readable web data, and can be found in products as diverse as Google's Knowledge Graph, online research repositories like Figshare, and other sources that engage in platformizing knowledge. The first paper in this panel examines the international Schema.org collaboration. The second paper investigates the epistemological implications when platforms organize data sharing. The third paper argues for the use of patents to inform research methodologies for understanding knowledge graphs. The fourth paper discusses private platforms’ extraction and collection of user metadata and the enclosure of data access.


2014 ◽  
Vol 543-547 ◽  
pp. 503-508
Author(s):  
Xin Ying Wang

IEC 61400-25 is a series of international standards on communication of wind power plants. The service defined by information exchange models in wind power plants communicates through being mapped to web service. Web service is described by WSDL, but with the limitation of WSDL itself, web service can not realize the semantic description, the automatic discovery and composition of service. So semantic web service is introduced, the service is described by OWL-S to realize the interconnection of wind power plant hardware devices from different manufacturers, to facilitate the sharing and reuse of devices function and to realize the sharing of wind power plant knowledge in semantic level.


Author(s):  
Sourav Maitra ◽  
A. C. Mondal

End users also start days with Internet. This has become the scenario. One of the most burgeoning needs of computer science research is research on web technologies and intelligence, as that has become one of the most emerging nowadays. A big area of other research areas like e-marketing, e-learning, e-governance, searching technologies, et cetera will be highly benefited if intelligence can be added to the Web. The objective of this chapter is to create a clear understanding of Web technology research and highlight the ways to implement Semantic Web. The chapter also discusses the tools and technologies that can be applied to develop Semantic Web. This new research area needs enough care as sometimes data are open. Thus, software engineering issues are also a focus.


Author(s):  
Jakub Flotyński ◽  
Athanasios G. Malamos ◽  
Don Brutzman ◽  
Felix G. Hamza-Lup ◽  
Nicholas F. Polys ◽  
...  

The implementation of virtual and augmented reality environments on the web requires integration between 3D technologies and web technologies, which are increasingly focused on collaboration, annotation, and semantics. Thus, combining VR and AR with the semantics arises as a significant trend in the development of the web. The use of the Semantic Web may improve creation, representation, indexing, searching, and processing of 3D web content by linking the content with formal and expressive descriptions of its meaning. Although several semantic approaches have been developed for 3D content, they are not explicitly linked to the available well-established 3D technologies, cover a limited set of 3D components and properties, and do not combine domain-specific and 3D-specific semantics. In this chapter, the authors present the background, concepts, and development of the Semantic Web3D approach. It enables ontology-based representation of 3D content and introduces a novel framework to provide 3D structures in an RDF semantic-friendly format.


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