The bits of text in question are generally short and straightforward, and the topic is well defined, so NLP software has a good chance of interpreting it correctly.Another start-up, Fast Search & Transfer Fastt), based in Norway, touts a more easily understood benefit of its software: that it is fast.
Natural-language processing (NLP), the ultimate goal of which is to enable computers to make sense of human languages, is an ambitious project with a very long way to go.
The technical jargon for it is natural language processing (NLP).
There are lots of things you can do, including using relaxation, visualisation and various nlp techniques.
Its algorithms are crafted using natural language processing (NLP) techniques and are tuned separately for each language to take account of structural differences.
Its successes beginning in the late 1980s and early 90s came as something of a surprise to the NLP community, which had been rather pessimistic about MT prospects ever since the report by Bar-Hillel (1960) and the ALPAC report (Pierce et al. 1966), negatively assessing the results of a major post-WW2 funding push in MT by the US government.
Also the statistical NLP community has developed remarkably comprehensive toolkits for researchers, such as MALLET (MAchine Learning for LanguagE Toolkit), which includes brief explanations of many of the techniques.
Any science (not art)[30] needs to fulfill three main requirements: first, it should have subject matter (DOS 167; 221); second, it should present the parts and species of a science's subject matter and their properties (DOS 650 652); third, it should take into account the first common principles of demonstration and have a set principles appropriated to its genus (NLP I.23).
The modus sciencie, according to the prologue of his NLPery, "consists of the speculation about the proven properties of the parts and species of the subject matter" (Lewry Pery, 382; see also NLP prologue; LT 50, 125), which is done by means of definition, division, and collection.
But one needs to proceed from what is better known to us (that is, that which is immediate in sense perception, the singular thing) to what is better known by nature or more removed from the senses (DOS 238; see also NLP I.7, 39; NSLP 18, 139 140), as scientific knowledge is not about the particular object immediately perceived but the universal (DOS 436).
The system was not developed to the point of practical usefulness, but its integration of reasoning and NLP technologies and its methods of selectively retrieving axioms for inferential QA were noteworthy contributions.
