Day by day the volume of information availability in the web is growing significantly. There are several data structures for information available in the web such as structured, semi-structured and unstructured. Majority of information in the web is presented in web pages. The information presented in web pages is semi-structured. But the information required for a context are scattered in different web documents. It is difficult to analyze the large volumes of semi-structured information presented in the web pages and to make decisions based on the analysis. The current research work proposed a frame work for a system that extracts information from various sources and prepares reports based on the knowledge built from the analysis. This simplifies  data extraction, data consolidation, data analysis and decision making based on the information presented in the web pages.The proposed frame work integrates web crawling, information extraction and data mining technologies for better information analysis that helps in effective decision making.  It enables people and organizations to extract information from various sourses of web and to make an effective analysis on the extracted data for effective decision making. The proposed frame work is applicable for any application domain. Manufacturing,sales,tourisum,e-learning are various application to menction few.The frame work is implemetnted and tested for the effectiveness of the proposed system and the results are promising.

The paper addresses two main problems of sports video processing: semantic segmentation and event detection. The theme is domain specific approach which exploits the typical characteristics of cricket video to design the most effective approach for the semantic segmentation and event detection which supports, efficient and effective retrieval of video scenes. Cricket video has been selected as the primary application, because they attract viewer worldwide and the complexity of the game is high. This paper proposes a novel hybrid multilayered approach for semantic segmentation of cricket video and major cricket events detection. The approach uses low level features and high level semantics with the rule based approach. The top layer uses the DLER tool to extract and recognize the super imposed text and the bottom layer applies the game rules to detect the boundaries of the video segments and major cricket events. The proposed model has been implemented, tested and the results are promising. Future work has been discussed at the end.