||Nowadays, handheld devices become more and more popular and are capable of browsing the contents with complicated web format. However, due to the limited network bandwidth and screen size of mobile phones, it is hard to read web contents without any information classifications. In this research, a system is developed to enable transforming web contents to OSGi Bundles based on document similarity. Related web contents are automatically grouped together based on their document similarities. User-selected web contents can be downloaded and packaged as an OSGi bundle, and furthermore, can be composed by service composition engines.|
|| The OSGi Alliance, 2003, OSGi Service Platform, Release 3, IOS Press, pages 604.|
 OSGi Service Platform, Core Specification, Release 4, Version 4.1, OSGi Alliance, 2007, pages 228.
 OSGi Service Platform, Mobile Specification, Release 4, Version 4, OSGi Alliance, 2007, pages 426.
 Scott Deerwester, Susan T Dumais, George W Furnas, Thomas K Landauer, Richard..., “Indexing by latent semantic analysis”, Journal of the American Society for Information Science (1986-1998), Sep 1990, pages. 391
 Thomas K Landauer, Peter W. Foltz & Darrell Laham, “An introduction to latent semantic analysis”, Discourse Processes, Vol 25(2-3), 1998, pages 259-284.
 Latent Semantic Analysis and Indexing
 Juan Ramos, “Using TF-IDF to Determine Word Relevance in Document Queries”, Department of Computer Science, Rutgers University, 23515
 Mehran Sahami, Timothy D. Heilman, “A web-based kernel function for measuring the similarity of short text snippets”, Proceedings of the 15th international conference on World Wide Web, Pages 377-386.
 Cosine Similarity and Term Weight Tutorial
 Gerard Salton, “Developments in Automatic Text Retrieval”, Science 30 August 1991, pages 974-980.