Corporate systems

The third on the list are the turnkey solutions based on the searching technologies. They are meant for serious companies and corporations, possessing really large data bases and staffed with all sorts of information systems and documents. In principle, the technologies themselves can also be used for home needs. For example, a programmer working remotely from the office will make good use of the search to access randomly located on his hard drive program source codes. But these are particulars. The main full text search application of the technology is still solving the problem of quickly and accurately searching through large data volumes and working with various information sources. Such information retrieval systems usually operate by a very simple scheme (although there are undoubtedly numerous unique methods of indexing and processing queries underneath the surface): phrasal search, with proper consideration for all the stem forms, synonyms etc. which once again leads us to the problem of human resource. When using such technology the user should first word the query phrases which are going to be the search criteria and presumably met in the necessary documents to be retrieved. But there is no guarantee that the user will be able to independently choose or remember the correct phrase and furthermore, that the search by this phrase will be satisfactory. One more key moment is the speed of processing a query. Of course, when using the whole document instead of a couple of words, the accuracy of search increases manifold. But up to date, such an opportunity has not been used because of the high capacity drain of such a process. The point is that search by words or phrases will not provide us with a highly relevant similarity of results. And the search by phrase equal in its length the whole document consumes much time and computer resources. Here is an example: while processing the query by one word there is no considerable difference in speed: whether it’s 0,1 or 0,001 second is not of crucial importance to the user. But when you take an average size document which contains about 2000 unique words, then the search with consideration for morphology (stem forms) and thesaurus (synonyms), as well as generating a relevant list of results in case of search by key words will take several dozens of minutes (which is unacceptable for a user).