i want uml diagrams for my final year projec of desktop search engine

uml diagrams for desktop search engine

Desktop search tools search within a user's own computer files as opposed to searching the Internet. These tools are designed to find information on the user's PC, including web browser history, e-mail archives, text documents, sound files, images, and video.

One of the main advantages of desktop search programs is that search results are displayed quickly due to the use of proper indexes.

A variety of desktop search programs are now available; see this list for examples.

Desktop search emerged as a concern for large firms for two main reasons: untapped productivity and security. On the one hand, users need to be able to quickly find relevant files, but on the other hand, they shouldn't have access to restricted files. According to analyst firm Gartner, up to 80% of some companies' data is locked up inside unstructured data — the information stored on an end user's PC, the directories (folders) and files they've created on a network, documents stored in repositories such as corporate intranets and a multitude of other locations.[1] Moreover, many companies have structured or unstructured information stored in older file formats to which they don't have ready access.

Companies doing business in the United States are frequently required under regulatory mandates like Sarbanes-Oxley, HIPAA and FERPA to make sure that access to sensitive information is 100% controlled. This creates a challenge for IT organizations, which may not have a desktop search standard, or lack strict central control over end users downloading tools from the Internet. Some consumer-oriented desktop search tools make it possible to generate indexes outside the corporate firewall and share those indexes with unauthorized users. In some cases, end users are able to index — but not preview — items they should not even know exist.[citation needed]

Historically, full desktop search comes from the work of Apple Computer's Advanced Technology Group, resulting in the underlying AppleSearch technology in the early 1990s. It was used to build the Sherlock search engine and then developed into Spotlight, which brought automated, non-timer-based full indexing into the operating system.