Using Data Mining for Facilitating User Contributions in the Social Semantic Web

Nonfiction, Computers, Internet
Cover of the book Using Data Mining for Facilitating User Contributions in the Social Semantic Web by Maryam Ramezani, GRIN Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Maryam Ramezani ISBN: 9783656047087
Publisher: GRIN Publishing Publication: November 4, 2011
Imprint: GRIN Publishing Language: English
Author: Maryam Ramezani
ISBN: 9783656047087
Publisher: GRIN Publishing
Publication: November 4, 2011
Imprint: GRIN Publishing
Language: English

Doctoral Thesis / Dissertation from the year 2011 in the subject Computer Science - Internet, New Technologies, grade: 1,0, Karlsruhe Institute of Technology (KIT), language: English, abstract: Social Web applications have emerged as powerful applications for Internet users allowing them to freely contribute to the Web content, organize and share information, and utilize the collective knowledge of others for discovering new topics, resources and new friends. While social Web applications such as social tagging systems have many benefits, they also present several challenges due to their open and adaptive nature. The amount of user generated data can be extremely large and since there is not any controlled vocabulary or hierarchy, it can be very difficult for users to find the information that is of their interest. In addition, attackers may attempt to distort the system's adaptive behavior by inserting erroneous or misleading annotations, thus altering the way in which information is presented to legitimate users. This thesis utilizes data mining and machine learning techniques to address these problems. In particular, we design and develop recommender systems to aid the user in contributing to the Social Semantic Web. In addition, we study intelligent techniques to combat attacks against social tagging systems. In our work, we first propose a framework that maps domain properties to recommendation technologies. This framework provides a systematic approach to find the appropriate recommendation technology for addressing a given problem in a specific domain. Second, we improve existing graph-based approaches for personalized tag recommendation in folksonomies. Third, we develop machine learning algorithms for recommendation of semantic relations to support continuous ontology development in a social semanticWeb environment. Finally, we introduce a framework to analyze different types of potential attacks against social tagging systems and evaluate their impact on those systems.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Doctoral Thesis / Dissertation from the year 2011 in the subject Computer Science - Internet, New Technologies, grade: 1,0, Karlsruhe Institute of Technology (KIT), language: English, abstract: Social Web applications have emerged as powerful applications for Internet users allowing them to freely contribute to the Web content, organize and share information, and utilize the collective knowledge of others for discovering new topics, resources and new friends. While social Web applications such as social tagging systems have many benefits, they also present several challenges due to their open and adaptive nature. The amount of user generated data can be extremely large and since there is not any controlled vocabulary or hierarchy, it can be very difficult for users to find the information that is of their interest. In addition, attackers may attempt to distort the system's adaptive behavior by inserting erroneous or misleading annotations, thus altering the way in which information is presented to legitimate users. This thesis utilizes data mining and machine learning techniques to address these problems. In particular, we design and develop recommender systems to aid the user in contributing to the Social Semantic Web. In addition, we study intelligent techniques to combat attacks against social tagging systems. In our work, we first propose a framework that maps domain properties to recommendation technologies. This framework provides a systematic approach to find the appropriate recommendation technology for addressing a given problem in a specific domain. Second, we improve existing graph-based approaches for personalized tag recommendation in folksonomies. Third, we develop machine learning algorithms for recommendation of semantic relations to support continuous ontology development in a social semanticWeb environment. Finally, we introduce a framework to analyze different types of potential attacks against social tagging systems and evaluate their impact on those systems.

More books from GRIN Publishing

Cover of the book Analysis of Shelley's 'Ode to the West Wind' by Maryam Ramezani
Cover of the book The Role of Emotions in Effective Negotiations by Maryam Ramezani
Cover of the book MTV: The (r)evolution & impact between 1981 - 1994 by Maryam Ramezani
Cover of the book Shakespeare - The disturbing world of Richard III and Edmund by Maryam Ramezani
Cover of the book Iraq against the United States of America (events 2003-2004) by Maryam Ramezani
Cover of the book The Stigma of Severe Mental Illness to Male and Female Students of Psychology and MBA by Maryam Ramezani
Cover of the book The application of three major characteristics of liturgy as seen in the Rite of Christian Initiation of Adults to Pastoral Care of the Sick and Dying by Maryam Ramezani
Cover of the book Die österreichische Umsatzsteuernovelle 2010 by Maryam Ramezani
Cover of the book Zamiatin's novel 'We' is a novel of ideas. It fails to move us on a human level. Discuss by Maryam Ramezani
Cover of the book Is there still hope for the Doha Round? by Maryam Ramezani
Cover of the book Primary Socialization with street children in Rio de Janeiro by Maryam Ramezani
Cover of the book The Novel 'Tsotsi' and its Adaptation on Film by Maryam Ramezani
Cover of the book Towards Theorization of Postcolonial Literature in the Global Culture of the Integrated Spectacle by Maryam Ramezani
Cover of the book Environmental Risk Management - Strategic tool or PR-technique? by Maryam Ramezani
Cover of the book Air Traffic Control Communication by Maryam Ramezani
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy