Mining query-logs towards learning useful kick-off ontologies: an incentive to semantic web content creation

2011 ◽  
Vol 1 (4) ◽  
pp. 303 ◽  
Author(s):  
Konstantinos Kotis ◽  
Andreas Papasalouros ◽  
Manolis Maragoudakis
Keyword(s):  
Semantic Web ◽  
Web Content ◽  
Content Creation ◽  
Query Logs

Semantic Web mining for Content-Based Online Shopping Recommender Systems

2019 ◽  
Vol 15 (4) ◽  
pp. 41-56 ◽  
Author(s):  
Ibukun Tolulope Afolabi ◽  
Opeyemi Samuel Makinde ◽  
Olufunke Oyejoke Oladipupo
Keyword(s):  
Semantic Web ◽  
Recommender Systems ◽  
Web Mining ◽  
Online Shopping ◽  
Semantic Analysis ◽  
Second Phase ◽  
Web Content ◽  
Textual Data ◽  
Content Mining ◽  
Bayes Algorithm

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.

Recent Advances in Web3D Semantic Modeling

2020 ◽  
pp. 23-49
Author(s):  
Jakub Flotyński ◽  
Athanasios G. Malamos ◽  
Don Brutzman ◽  
Felix G. Hamza-Lup ◽  
Nicholas F. Polys ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Semantic Web ◽  
Web Content ◽  
3D Structures ◽  
Web Technologies ◽  
Domain Specific ◽  
Virtual And Augmented Reality ◽  
The Web ◽  
3D Web ◽  
3D Content

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.

A Review of Emerging Technological Trends in E-Learning

2011 ◽  
pp. 729-740
Author(s):  
Furkan Tari
Keyword(s):  
Information Technology ◽  
Semantic Web ◽  
Learning Outcomes ◽  
Learning Process ◽  
Learning Outcome ◽  
Learning Technologies ◽  
Web Content ◽  
Holistic View ◽  
Behavioral Issues ◽  
E Learning

Advances in information technology and the redefined web trigger a holistic view of learning process. The objective of this study is to provide a conceptual view of how various technologies can be used to maximize learning outcomes through e-learning. Among the trends investigated in this study are, XML and semantic Web, content-based video indexing, personalized, intelligent Web tutoring, and m-learning. In addition to these technologies, a brief review of some of the key behavioral issues is presented. For researchers and developers interested in maximizing the learning outcome through e-learning technologies, the paper provides a taxonomy of these trends along with a framework for future designs.

Combining Ontology with Intelligent Agent to Provide Negotiation Service

2010 ◽  
Vol 2 (3) ◽  
pp. 52-61 ◽  
Author(s):  
Qiumei Pu ◽  
Yongcun Cao ◽  
Xiuqin Pan ◽  
Siyao Fu ◽  
Zengguang Hou
Keyword(s):  
Semantic Web ◽  
Information Exchange ◽  
Intelligent Agent ◽  
Direct Impact ◽  
Web Content ◽  
Communication Architecture ◽  
Negotiation Protocol ◽  
Communication Framework ◽  
Research Areas ◽  
Cross Platform

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.

Automatically Extracting and Tagging Business Information for E-Business Systems Using Linguistic Analysis

2007 ◽  
pp. 101-126
Author(s):  
Sumali Conlon ◽  
Susan Lukose ◽  
Jason G. Hale ◽  
Anil Vinjamur
Keyword(s):  
Semantic Web ◽  
Language Processing ◽  
Linguistic Analysis ◽  
Prototype System ◽  
Web Content ◽  
Business Systems ◽  
Web Documents ◽  
Business Applications ◽  
Extensible Markup ◽  
Automated Processing

The Semantic Web will require semantic representations of information that computers can understand when they process business applications. Most Web content is currently represented in formats such as text, that facilitate human understanding, rather than in the more structured formats, that allow automated processing and computer understanding. This chapter explores how natural language processing (NLP) principles, using linguistic analysis, can be employed to extract information from unstructured Web documents and translate it into extensible markup language (XML)—the enabling currency of today’s e-business applications, and the foundation for the emerging Semantic Web languages of tomorrow. Our prototype system is built and tested with online financial documents.

Representing and Sharing Tagging Data Using the Social Semantic Cloud of Tags

2010 ◽  
pp. 519-527
Author(s):  
Hak-Lae Kim ◽  
John G. Breslin ◽  
Stefan Decker ◽  
Hong-Gee Kim
Keyword(s):  
Semantic Web ◽  
Web 2.0 ◽  
Web Applications ◽  
Essential Element ◽  
Social Tagging ◽  
Social Software ◽  
Free Text ◽  
Content Creation ◽  
Software Applications ◽  
The Social

Social tagging has become an essential element for Web 2.0 and the emerging Semantic Web applications. With the rise of Web 2.0, websites that provide content creation and sharing features have become extremely popular. These sites allow users to categorize and browse content using tags (i.e., free-text keyword topics). However, the tagging structures or folksonomies created by users and communities are often interlocked with a particular site and cannot be reused in a different system or by a different client. This chapter presents a model for expressing the structure, features, and relations among tags in different Web 2.0 sites. The model, termed the Social Semantic Cloud of Tags (SCOT), allows for the exchange of semantic tag metadata and reuse of tags in various social software applications.

scholarly journals BioAssay Templates for the semantic web

2016 ◽  
Vol 2 ◽  
pp. e61 ◽  
Author(s):  
Alex M. Clark ◽  
Nadia K. Litterman ◽  
Janice E. Kranz ◽  
Peter Gund ◽  
Kellan Gregory ◽  
...  
Keyword(s):  
Semantic Web ◽  
Degrees Of Freedom ◽  
Software Tool ◽  
Data Format ◽  
Content Creation ◽  
Software Algorithms ◽  
Pertinent Information ◽  
Low Degrees ◽  
Machine Readable ◽  
Community Input

Annotation of bioassay protocols using semantic web vocabulary is a way to make experiment descriptions machine-readable. Protocols are communicated using concise scientific English, which precludes most kinds of analysis by software algorithms. Given the availability of a sufficiently expressive ontology, some or all of the pertinent information can be captured by asserting a series of facts, expressed as semantic web triples (subject, predicate, object). With appropriate annotation, assays can be searched, clustered, tagged and evaluated in a multitude of ways, analogous to other segments of drug discovery informatics. The BioAssay Ontology (BAO) has been previously designed for this express purpose, and provides a layered hierarchy of meaningful terms which can be linked to. Currently the biggest challenge is the issue of content creation: scientists cannot be expected to use the BAO effectively without having access to software tools that make it straightforward to use the vocabulary in a canonical way. We have sought to remove this barrier by: (1) defining a BioAssay Template (BAT) data model; (2) creating a software tool for experts to create or modify templates to suit their needs; and (3) designing a common assay template (CAT) to leverage the most value from the BAO terms. The CAT was carefully assembled by biologists in order to find a balance between the maximum amount of information captured vs. low degrees of freedom in order to keep the user experience as simple as possible. The data format that we use for describing templates and corresponding annotations is the native format of the semantic web (RDF triples), and we demonstrate some of the ways that generated content can be meaningfully queried using the SPARQL language. We have made all of these materials available as open source (http://github.com/cdd/bioassay-template), in order to encourage community input and use within diverse projects, including but not limited to our own commercial electronic lab notebook products.

scholarly journals IT Gaining Ground in Learning

2013 ◽  
Vol 8-9 ◽  
pp. 37-44 ◽  
Author(s):  
Iasmina Leila Ermalai
Keyword(s):  
Semantic Web ◽  
Question Answering ◽  
Online Courses ◽  
Content Management ◽  
General Context ◽  
Web Content ◽  
Personal Learning ◽  
Video Lectures ◽  
Web Standards ◽  
Audio Video

Continuously emerging forms of eLearning like MOOC (Massive Open Online Courses), PLE (Personal Learning Environment) and the use of Semantic Web standards in learning environments, are consistent proof that IT, the Internet, the World Wide Web, Content Management Systems, audio/video lectures, videoconferences, Semantic Web are here to stay, evolve and furthermore, to take control of the learning process, making from it a flexible, viable, profitable and extensively used solution for delivering knowledge. In this general context, the present paper offers an eLearning state-of-the-art and an overview of the trends and technologies proposed, developed and implemented in a particular eLearning environment, over the last years, as part of a postdoctoral research program. The mentioned environment was the Moodle portal used at the “Politehnica” University of Timisoara, the implemented standards were the hCard and hCalendar microformats and the proposed model was one of collective learning through question answering.

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