text mining and text analytics while language isn' limited to the natural languagethe focus of this will be on natural language processing (nlpexamples of non-natural languages would be machine logsmathematicsand morse code technically even esperantoklingonand dragon language aren' in the field of natural languages because they were invented deliberately instead of evolving over timethey didn' come "naturalto us these last languages are nevertheless fit for natural communication (speechwriting)they have grammar and vocabulary as all natural languages doand the same text mining techniques could apply to them text mining in the real world in your day-to-day life you've already come across text mining and natural language applications autocomplete and spelling correctors are constantly analyzing the text you type before sending an email or text message when facebook autocompletes your status with the name of friendit does this with the help of technique called named entity recognitionalthough this would be only one component of their repertoire the goal isn' only to detect that you're typing nounbut also to guess you're referring to person and recognize who it might be another example of named entity recognition is shown in figure google knows chelsea is football club but responds differently when asked for person google uses many types of text mining when presenting you with the results of query what pops up in your own mind when someone says "chelsea"chelsea could be many thingsa persona soccer cluba neighborhood in manhattannew york or londona food marketa flower showand so on google knows this and returns different answers to the question "who is chelsea?versus "what is chelsea?to provide the most relevant answergoogle must do (among other thingsall of the followingpreprocess all the documents it collects for named entities perform language identification detect what type of entity you're referring to match query to result detect the type of content to return (pdfadult-sensitivethis example shows that text mining isn' only about the direct meaning of text itself but also involves meta-attributes such as language and document type google uses text mining for much more than answering queries next to shielding its gmail users from spamit also divides the emails into different categories such as socialupdatesand forumsas shown in figure it' possible to go much further than answering simple questions when you combine text with other logic and mathematics