Encyclopedia of Computer Science and Technology

330 natural language processingplace of copper wires as conductors in computer chips. Aschips continue to shrink, the connectors have also had toget smaller, but this in turn increases electrical resistanceand reduces efficiency. Nanotubes, however, are not onlysuperb electrical conductors, they are also far thinner thantheir copper counterparts. Intel Corporation has conductedpromising tests of nanotube conductors, but it will likely bea number of years before they can be manufactured on anindustrial scale.An obstacle to manufacturing carbon nanotubes is thateach newly made batch is a mixture of “metallic” (conducting)and semiconducting tubes of different diameters.Manufacturing, however, requires tubes that meet strictrequirements. Fortunately researchers at NorthwesternUniversity in 2006 developed a way to sort the tubes byadding substances that changed their density according toboth their diameter and their electrical conductivity.Another alternative is “nanowires.” One design consistsof a germanium core surrounded by a thin layer of crystallinesilicon. Nanowires are easier to manufacture thannanotubes, but their performance and other characteristicsmay make them less useful for general-purpose computingdevices.The ultimate goal is to make the actual transistors incomputer chips out of nanotubes instead of silicon. Animportant step in this direction was achieved in 2006 byIBM researchers who created a complete electronic circuitusing a single carbon nanotube molecule.Further ReadingBooker, Richard D. and Earl Boysen. Nanotechnology for Dummies.Hoboken, N.J.: Wiley, 2005.Bullis, Kevin. “Nanotube Computing Breakthrough: A Method forSorting Nanotubes by Electronic Properties Could Help MakeWidespread Nanotube-Based Electronics a Reality.” TechnologyReview, October 30, 2006. Available online. URL: http://www.technologyreview.com/Nanotech/17672/. Accessed August 16,2007.———. “Nanowire Transistors Faster than Silicon.” TechnologyReview, June 20, 2006. Available online. URL: http://www.technologyreview.com/Nanotech/17008/. Accessed August16, 2007.Edwards, Steven A. The Nanotech Pioneers: Where Are They TakingUs? New York: Wiley, 2006.Kanellos, Michael. “Intel Eyes Nanotubes for Future Chip Designs.”CNET News, November 10, 2006. Available online. URL: http://news.com.com/2100-1008_3-6134437.html. Accessed August16, 2007.Korkin, Anatoli, et al., eds. Nanotechnology for Electronic Materialsand Devices. New York: Springer, 2007.Nanotech Web. Available online. URL: http://nanotechweb.org/.Accessed August 16, 2007.natural language processingSince at least the days of Hal 9000 and early Star Trek, thecomputer of the future was supposed to be able to understandwhat people wanted, when expressed in ordinary languageand not programming code. Computer scientists havebeen working on this capability, called natural languageprocessing (NLP), for decades.NLP is a multidisciplinary field that draws from linguisticsand computer science, particularly artificial intelligence(see also linguistics and computing and speech recognitionand synthesis). In terms of linguistics, a programmust be able to deal with words that have multiple meanings(“wind up the clock” and “the wind is cold today”) aswell as grammatical ambiguities (in the phrase “little girl’sschool” is it the school that is little, the girls, or both?). Ofcourse each language has its own forms of ambiguity.Programs can use several strategies for dealing withthese problems, including using statistical models to predictthe likely meaning of a given phrase based on a “corpus” ofexisting text in that language (see language translationsoftware).As formidable as the task of extracting the correct (literal)meaning from text can be, it is really only the first levelof natural language processing. If a program is to successfullysummarize or draw conclusions about a news reportfrom North Korea, for example, it would also have to havea knowledge base of facts about that country and/or a set of“frames” (see Minsky, Marvin) about how to interpret varioussituations such as threat, bluff, or compromise.)ApplicationsThere are a variety of emerging applications for NLP, includingthe following:• voice-controlled computer interfaces (such as in aircraftcockpits)• programs that can assist with planning or other tasks(see software agents)• more-realistic interactions with computer-controlledgame characters• robots that interact with humans in various settingssuch as hospitals• automatic analysis or summarization of news storiesand other text• intelligence and surveillance applications (analysis ofcommunication, etc.)• data mining, creating consumer profiles, and other e-commerce applications• search-engine improvements, such as in determiningrelevancyFurther ReadingJackson, Peter, and Isabelle Moulinier. Natural Language Processingfor Online Applications: Text Retrieval, Extraction and Categorization.2nd ed. Philadelphia: John Benjamins, 2007.Kao, Anne, and Steve R. Poteet, eds. Natural Language Processingand Text Mining. New York: Springer, 2007.Manning, Christopher D., and Hinrich Schütze. Foundations ofStatistical Natural Language Processing. Cambridge, Mass.:MIT Press, 1999. Available online. URL: http://www-nlp.stanford.edu/fsnlp/. Accessed October 4, 2007.Natural Language Toolkit. Available online. URL: http://nltk.sourceforge.net/index.php/Main_Page. Accessed October 4,2007.