From Web Data to Visualization via Ontology Mapping

نویسندگان

  • O. Gilson
  • Nuno Silva
  • Phil W. Grant
  • Min Chen
چکیده

In this paper, we propose a novel approach for automatic generation of visualizations from domain-specific data available on the web. We describe a general system pipeline that combines ontology mapping and probabilistic reasoning techniques. With this approach, a web page is first mapped to a Domain Ontology, which stores the semantics of a specific subject domain (e.g., music charts). The Domain Ontology is then mapped to one or more Visual Representation Ontologies, each of which captures the semantics of a visualization style (e.g., tree maps). To enable the mapping between these two ontologies, we establish a Semantic Bridging Ontology, which specifies the appropriateness of each semantic bridge. Finally each Visual Representation Ontology is mapped to a visualization using an external visualization toolkit. Using this approach, we have developed a prototype software tool, SemViz, as a realisation of this approach. By interfacing its Visual Representation Ontologies with public domain software such as ILOG Discovery and Prefuse, SemViz is able to generate appropriate visualizations automatically from a large collection of popular web pages for music charts without prior knowledge of these web pages.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Development of a Combined System Based on Data Mining and Semantic Web for the Diagnosis of Autism

Introduction: Autism is a nervous system disorder, and since there is no direct diagnosis for it, data mining can help diagnose the disease. Ontology as a backbone of the semantic web, a knowledge database with shareability and reusability, can be a confirmation of the correctness of disease diagnosis systems. This study aimed to provide a system for diagnosing autistic children with a combinat...

متن کامل

Development of a Combined System Based on Data Mining and Semantic Web for the Diagnosis of Autism

Introduction: Autism is a nervous system disorder, and since there is no direct diagnosis for it, data mining can help diagnose the disease. Ontology as a backbone of the semantic web, a knowledge database with shareability and reusability, can be a confirmation of the correctness of disease diagnosis systems. This study aimed to provide a system for diagnosing autistic children with a combinat...

متن کامل

Designing an Ontology for Knowledge Discovery in Iran’s Vaccine

Ontology is a requirement engineering product and the key to knowledge discovery. It includes the terminology to describe a set of facts, assumptions, and relations with which the detailed meanings of vocabularies among communities can be determined. This is a qualitative content analysis research. This study has made use of ontology for the first time to discover the knowledge of vaccine in Ir...

متن کامل

Query Architecture Expansion in Web Using Fuzzy Multi Domain Ontology

Due to the increasing web, there are many challenges to establish a general framework for data mining and retrieving structured data from the Web. Creating an ontology is a step towards solving this problem. The ontology raises the main entity and the concept of any data in data mining. In this paper, we tried to propose a method for applying the "meaning" of the search system, But the problem ...

متن کامل

Browser-based Semantic Mapping Tool for Linked Data in Semantic Web

With the ever growing need of semantically linking data across different domain, organizational and diplomacy boundaries using RDF and OWL, one of the major obstacles impeding the advancement of Semantic Web is the data availability. This paper presents a browser-based semantic mapping tool for converting linked data on the Web to be available for Semantic Web applications. It is aiming at help...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Comput. Graph. Forum

دوره 27  شماره 

صفحات  -

تاریخ انتشار 2008