Image Based Model for Document Search and Re-ranking

Traditional Web search engines do not use the images in the web pages to search relevant documents for a given query. Instead, they are typically operated by computing a measure of agreement between the keywords provided by the user and only the text portion of each web page. This project describes whether the image content appearing in a Web page can be used to enhance the semantic description of Web page and accordingly improve the performance of a keyword-based search engine. A Web-scalable system is presented in such a way that exploits a pure text-based search engine that finds an initial set of candidate documents as per given query. Then, by using visual information extracted from the images contained in the pages, the candidate set will be re-ranked. The computational efficiency of traditional text-based search engines will be maintained by the resulting system with only a small additional storage cost that will be needed to predetermine the visual information

Intrusion Detection and Anomaly Detection System Using Sequential Pattern Mining

Nowadays the security methods from password protected access up to firewalls which are used to secure the data as well as the networks from attackers. Several times these type of security methods are not enough to protect data. We can consider the use of Intrusion Detection Systems (IDS) is the one way to secure the data on critical systems. Most of the research work is going on the effectiveness and exactness of the intrusion detection, but these attempts are for the detection of the intrusions at the operating system and network level only. It is unable to detect the unexpected behavior of systems due to Malicious transactions in databases. The method used for spotting any interferes on the information in the form of database known as database intrusion detection. It relies on enlisting the execution of a transaction. After that, if the recognized pattern is aside from those regular patterns actual is considered as an intrusion. But the identified problem with this process is that the accuracy algorithm which is used may not identify entire patterns. This type of challenges can affect in two ways. 1) Missing of the database with regular patterns. 2) The detection process neglects some new patterns. Therefore we proposed sequential data mining method by using new Modified Apriori Algorithm. The algorithm upturns the accurateness and rate of pattern detection by the process. The Apriori algorithm with modifications is used in the proposed model