A Novel Spatial Tag Cloud Using Multi-Level Clustering

نویسندگان

  • Jen-Wei Huang
  • Kuan-Ying Chen
  • Yuan-Chang Chen
  • Kai-Ning Yang
  • I-Shyan Hwang
  • Wei-Che Huang
چکیده

Conventional tag cloud systems can only present the frequency of tags and the connection of tags and tag clusters, but cannot properly express the strength of the relationships. In this paper we tackle this problem by improving the representation of tag clustering. We combine the advantages of conventional systems to create a multi-level interactive tag cloud system using clustering scheme. In our tag cloud system, tags are mapped onto a two-dimensional space. A force-directed algorithm is applied to make the tags move in 2D space. The tags will move until equilibrium is reached. As a result, the tags with high correlation are clustered in the close vicinity, and so are the tag clusters with high correlation. In addition, we let the users to interact with the tag cloud by zooming and panning for different perspectives and let user to select a tag than the tag will locate at the center of window and show the correlations of the user selected tag with other tags. We believe that our system can improve the user browsing experience, and can also be served as a great basis for social network analysis and other related research.

برای دانلود 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

An efficient method for cloud detection based on the feature-level fusion of Landsat-8 OLI spectral bands in deep convolutional neural network

Cloud segmentation is a critical pre-processing step for any multi-spectral satellite image application. In particular, disaster-related applications e.g., flood monitoring or rapid damage mapping, which are highly time and data-critical, require methods that produce accurate cloud masks in a short time while being able to adapt to large variations in the target domain (induced by atmospheric c...

متن کامل

An Optimal Utilization of Cloud Resources using Adaptive Back Propagation Neural Network and Multi-Level Priority Queue Scheduling

With the innovation of cloud computing industry lots of services were provided based on different deployment criteria. Nowadays everyone tries to remain connected and demand maximum utilization of resources with minimum timeand effort. Thus, making it an important challenge in cloud computing for optimum utilization of resources. To overcome this issue, many techniques have been proposed ...

متن کامل

Methodologies for Improved Tag Cloud Generation with Clustering

Tag clouds are useful means for navigation in the social web systems. Usually the systems implement the tag cloud generation based on tag popularity which is not always the best method. In this paper we propose methodologies on how to combine clustering into the tag cloud generation to improve coverage and overlap. We study several clustering algorithms to generate tag clouds. We show that by e...

متن کامل

SimSpectrum: A Similarity Based Spectral Clustering Approach to Generate a Tag Cloud

Tag clouds are means for navigation and exploration of information resources on the web provided by social Web sites. The most used approach to generate a tag cloud so far is based on popularity of tags among users who annotate by those tags. This approach however has several limitations, such as suppressing number of tags which are not used often but could lead to interesting resources as well...

متن کامل

Bandwidth and Delay Optimization by Integrating of Software Trust Estimator with Multi-User Cloud Resource Competence

Trust Establishment is one of the significant resources to enhance the scalability and reliability of resources in the cloud environment. To establish a novel trust model on SaaS (Software as a Service) cloud resources and to optimize the resource utilization of multiple user requests, an integrated software trust estimator with multi-user resource competence (IST-MRC) optimization mechanism is...

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

برای دانلود 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

عنوان ژورنال:
  • J. Inf. Sci. Eng.

دوره 30  شماره 

صفحات  -

تاریخ انتشار 2014