What is text mining? |
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Limitations of Text MiningThe fundamental limitations of text mining are first, that we will not be able to write programs that fully interpret text for a very long time, and second, that the information one needs is often not recorded in textual form. If I tried to write a program that detected when a where a new word came into existence and how it spread by analyzing web pages, I would miss important clues relating to usage in spoken conversations, email, on the radio and TV, and so on. Similarly, If I tried to write a program that processes published documents in order to guess what will happen to a bill in Washington DC, I would fail because most of the action still happens in negotiations behind closed doors.Implications of Text miningUntil recently websites most often used text-based lexical searches; in other words, users could find documents only by the words that happened to occur in the documents. Text mining may allow searches to be directly answered by the semantic web; users may be able to search for content based on its meaning and context, rather than just by a specific word.Additionally, text mining software can be used to build large dossiers of information about specific people and events. For example, by using software that extracts specifics facts about businesses and individuals from news reports, large datasets can be built to facilitate social networks analysis or counter-intelligence. In effect, the text mining software may act in a capacity similar to an intelligence analyst or research librarian, albeit with a more limited scope of analysis. Text mining is also used in some email spam filters as a way of determining the characteristics of messages that are likely to be advertisements or other unwanted material. |
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