Google Wave: Natural Language Processing
Casey Whitelaw describes the natural language processing behind Google Wave's spelling correction on the deck of the Sydney office. Birds and boat horns for effect.
Lecture - 39 Natural Language Processing - I
Lecture Series on Artificial Intelligence by Prof.Sudeshna Sarkar and Prof.Anupam Basu, Department of Computer Science and Engineering,IIT, Kharagpur . For more details on NPTEL visit nptel.iitm.ac.in.
Natural Language Processing in Python
Shankar Ambady of Session M will give a tutorial on the Python NLTK (Natural Language Tool Kit). Shankar had previously presented a comprehensive overview of the NLTK last December at the Python meetup. The Python NLTK is a very powerful collection of libraries that can be applied to a variety of NLP applications such as sentiment analysis. His presentation from last December may be found here (click on Boston Python Meetup Materials) : www.shankarambady.com microsoftcambridge.com
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Natural Language Processing
Dan Jurafsky and Chris Manning will be teaching Natural Language Processing online in January. Sign up at nlp-class.org
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InteliWISE Natural Language Processing - How Does It Work?
Natural Language Processing (NLP) and Semantic Search in InteliWISE Virtual Self - Service Agents This short demo shows how InteliWISE Natural Language Processing and Semantic Search Engine can power Virtual Agents. Get those Agents from www.inteliwise.com.
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Lecture - 40 Natural Language Processing II
Lecture Series on Artificial Intelligence by Prof.Sudeshna Sarkar and Prof.Anupam Basu, Department of Computer Science and Engineering,IIT, Kharagpur . For more details on NPTEL visit nptel.iitm.ac.in.
The Truth About Sentiment & Natural Language Processing
Synthesio has traditionally relied on human analysts for sentiment but has the capacity to incorporate an automatic analysis. Here, we took a look at the pros and cons of text analytics and new technology that is available. Download the Synthesio white paper in English (bit.ly or French (bit.ly for more case studies and let us know if you use automatic or human analysis for sentiment, and what you have found from your own experiences !
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How Natural Language Processing is Changing Research
Aditi Muralidharan demonstrates how natural language processing has not only found its place in the humanities, but has also dramatically sped up the the time it takes to conduct research.
Semantics - A Look at Modern Day Natural Language Processing
Final project for Semantics 341 - University of Saskatchewan By Max Cranston A very simple video... a look at how modern day natural language processing has been affected by: the evolution of text editors increase in computer power in conjunction with Moore's Law evolution of technology research in linguistic fields chatterbots Grice's Maxims of cooperative conversation and a communication between two chatterbots I posted responses from each bot to the other, in order to create a conversation filmed using xtranormal's text to video software female: ALICE alice.pandorabots.com male: Jabberwacky www.jabberwacky.com
Semantics Linguistics Natural Language Processing Deep Blue Moore's Law maximumcranston
IBM Watson: Computer Understands Natural Language
IBM's Watson is a real time, natural language processing computer that employs deep analytics and machine learning capabilities to answer questions. Watson's ability will be tested on the game show Jeopardy! Visit ibmwatson.com for more information.
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Building Watson - A Brief Overview of the DeepQA Project
David Ferrucci of IBM discusses the DeepQA Project; the technology and architecture behind IBM's newest technological innovation, the question answering and natural language processing system, Watson. Visit ibmwatson.com for more information.
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Video 1: Theme Zoom versus Wordtracker: Natural Language Processing
Theme Zoom is not in competition with Word Tracker, because Word Tracker does not implement natural language processing. www.themezoom.com
Online Advertising Demo
OpenAmplify is a web service that brings human understanding to content. Using patented Natural Language Processing technology, OpenAmplify reads and understands every word used in text. It identifies the significant topics, brands, people, perspectives, emotions, actions and timescales and presents the findings in an actionable XML structure. By understanding what text actually means not just the individual words OpenAmplify can better manage and monetize content. The company has leveraged 20 years of academic research into applied computational linguistics and machine learning. Unlike most deep Natural Language Processing technologies, OpenAmplifys research has concentrated on commercial systems that meet the demands of large-scale business use.
openamplify Semantic Web Community Web Developers Web 3.0 Twitter Gmail Open Amplify
Where Human Language meets Computer Science
In this movie, we are using an artistic approach to communicate a scientific topic. Dr. Agnieszka "Bronka" Bronowska, a HITS researcher and artist, has designed and produced a video on computational linguistics. Technical devices are getting more versatile and sophisticated all the time. To make their use more intuitive, The Natural Language Processing group (NLP) at HITS (group leader: Prof. Michael Strube) develops software facilitating the multimodal dialogue between users and machines, applying both statistical and symbolic methods. The group's research focus lies on the semantics and pragmatics of discourse.
HITS natural Language processing NLP Michael Strube Computational linguistics Agnieszka Bronowska Bronka The hitsters
Reusable IT | Semantic Enterprise Search Engine
Semantic Box is the next generation enterprise search engine that combines Semantic and Natural Language Processing state of the art technology to improve user experience and deliver the most precise search results.
Reusable IT Semantic Enterprise Search Natural Language Processing reusableit
Perspectives on Watson - Ambiguity
IBM's Watson is a deep analytics and natural language processing computer that has tackled the issue of processing and recognizing ambiguous words, allowing it to compete on Jeopardy!. Visit ibmwatson.com for more information.
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IBM Watson: The Science Behind an Answer
After Watson's groundbreaking performance on Jeopardy!, see how this incredible smart technology processes data. In this video, the four steps of Watson's question answering technology are covered, along with what the future holds for IBM's intelligent natural language processing platform beyond Jeopardy!
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The Blackhole Web App
The Blackhole is a web application abstracting the details of file management into an object called the Blackhole. It uses pseudo natural language processing to retrieve the files a user queries.
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IBM Watson: The Next Grand Challenge
In the tradition of IBM's grand challenges such as Deep Blue with chess and Blue Gene with the human genome, Watson is the next scientific breakthrough with natural language processing on Jeopardy. Visit ibmwatson.com for more information.
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Articulate: a Conversational Interface for Visual Analytics
'Articulate' is a methodology that uses natural language to interact with visualizations. It is part of 'Project Lifelike' - a research initiative to provide a more natural alternative for interacting with computers. As computing becomes more accessible through the Internet, and more recently mobile phone applications, there is renewed interest in organic and seamless ways to harness the power of this technology. Human speech is a promising and attractive approach. 'Articulate' is a system that applies natural language processing and machine learning techniques in the area of data visualization and analysis. Its goal is to automatically translate natural language queries into meaningful representations of data. 'Articulate' incorporates a natural language parser with machine learning algorithms to translate spoken language. The user's input sentence is parsed into a syntactic tree tagged with part-of-speech labels, from which a feature vector can be extracted to represent the query. Based on this set of features, a supervised learning algorithm identifies the intended visual analytic task, which is used to guide a graph generation algorithm in determining the appropriate visualization to present to the user. The ultimate goal of this research is to allow users to employ advanced visualization techniques without the burden of first having to learn a complex or cumbersome user interface. 'Articulate' is a step towards a time when computers will understand the user's <b>...</b>
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