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Many users searching databases through the web in various domains like vehicles, real estate, etc. One of the predicament, we observed in this task is ranking the results retrieved from a database for a user query. The contemporary methods are addressing this problem by sorting the database values. A common line in these methods is that ranking is done in a user and query-independent manner i.e. there is no correspondence between different users queries. We proposed a query and user-dependent approach for ranking query results in relational databases, which is articulating the opinion expressed in query by different users. The designed and developed methodology shows that the ranking of the data in database is constituted depending on the various user opinions i.e. access of tuple through users query expression. The design is based on counting the access of database tuple by users query(ies)

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while many financiers use the Internet and social media to help them with investment decisions, these online tools can provide many benefits for investors and at the same time, same tools can make smart objectives for lawbreakers. These offenders are quick to adapt to new technologies-and Social media is no exception. Social media, such as Facebook, YouTube, Twitter, and LinkedIn, have become key tools for investors worldwide. Whether they are seeking study on particular stocks, background information on a broker-dealer or investment consultant, guidance on an overall investment strategy, up to date news or to simply want to the markets with others, investors turn to social media. Social media also offers a number of features that criminals may find attractive. Fraudsters can use social media in their efforts to appear legitimate, to hide behind anonymity, and to reach many people at low cost.