Context oriented analysis of web 2.0 social network contents-MindMeister use-case

ABSTRACT

Web 2.0 has changed the technological landscape of the Internet computing world today. The shift from traditional web which is also known as Web 1.0 is forced by the growing need for more efficient information sharing, collaboration, and business processes. The disclosure of personal/organizational information in Web 2.0 via social networks, digital contributions and data feeds has created new security and privacy challenges. Designing transparent, usable systems in support of personal privacy, security, and trust, requires advanced knowledge retrieval techniques that can support information sharing processes by applying appropriate policies. This paper proposes an improved Word Sense Disambiguation methodology that combines the existing WSD techniques with semi-structured Web 2.0 contents to achieve a more accurate semantic annotation of the text. The resulted quality indicator will support the implementation of some useful scenarios such as content query, knowledge retrieval, and security and privacy use-cases. To provide a better validation of the proposed solution, it will be explored in context of the MindMeister mind mapping tool.

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Index Terms

• Hardware

  • Power and energy

    • Power estimation and optimization

      • Platform power issues

• Information systems

  • Information retrieval