NanoSyntax:  Natural Language Processing

 

Group 1

 

Alton Barnes, Laura Elser, Meghan Engel, Jordon Lieblong, Kevin Young

 

Key Words:  Linguistic Agents, Natural Language, NanoSyntax

 

For over four decades natural language processing has been fantasy in the computer world.  Natural language processing, also known as NLP, is the process of computers breaking the code of natural language. The human brain processes language through encoded packages, but older NLPs process language using statistic models decoding sentences.  There have been many attempts to allocate computers to understand human language by dozens of commercial companies and universities.  A company named Linguistic Agents created the new and improved version of NLP named NanoSyntax, which has made the code breaking process of natural language possible.  The company’s new approach to understanding human language is based on linguistic rules and encryption of sentences.  Linguistic Agents’ software is the only natural language software in the market that has this new technology, giving them an immense competitive advantage.  This innovative software will allow this company to partner with many additional companies, and will create better solutions for NLP processing.  The implementation of improved NLP will allow better search engines, Internet gaming, educational software and improved automated systems.

 

Linguistic Agents’ software is the only natural language software available today based on the latest linguistic theory, NanoSyntax.  Linguistic Agents (L.A.) has been building a full Nanosyntactic Linguistic tree that enables computers to understand the true meaning of complex sentences.  L.A.’s advanced parsing algorithm can resolve very subtle cases of ambiguity and easily recognizes and processes negations, comparatives, quantifiers, etc.  It also allows software applications to execute commands, answer questions, get more accurate search results, and increase the relevance of context-based advertising.  This powerful technology operates on minimal system resources, allowing for seamless integration into existing and new applications in a wide array of applications.

 

Linguistic Agents seeks to resolve an almost inherent failure in the communication between man and computer, and to educate computers to receive instructions from humans in a natural and intuitive language.  To date, the company has received $1.1 million in financing from private investors for research on natural language processing.  Every sentence spoken by a human being can be broken down into two different types of understanding.  One type is known as “shallow structure”, it is the basic understanding of the specific sentence, and this understanding is unique to the specific sentence.  The second type is known as “deep structure”, which is the root of understanding of the sentence and is the same for all sentences that have the same meaning even if the sentences are in different languages.  Most natural language applications use a shallow-parsing algorithm to extract certain parts of the data contained in the sentence.  This allows these applications to do a limited amount of natural language processing


and, therefore, get limited results.  When using a deep-parsing algorithm, all sentences with the same meaning have the same output.  This allows for better natural language interfacing, as well as the ability to use the output in a multitude of other applications.

 

Linguistic Agents (L.A.) has created an application that allows computers to understand human language.  L.A. is a branch of the Israel Company’s Advanced Language Machine; and their founder and CEO is Sasson Margaliot.  L.A. uses NanoSyntax technology to break down the human language into parts and understand the meaning of sentences.  Computational linguistics works to understand the meaning of every word in the sentence, instead of understanding the meaning of the phrase or sentence. 

 

Linguistic Agents wanted to figure out a way to take sentences and convert the information into a format that the linguistic tree would understand.  Running the sentences through the linguistic tree enables the computer to understand the meaning of the sentence.  Linguistic technology is like an advanced search engine. This search engine will be more valuable to people by making these intelligent devices more user-friendly.   

 

Before the introduction of NanoSyntax, most companies used statistical models to decode sentences, meaning that the systems learn over time to identify the users’ true intentions.  But with the ability to translate normative human language into a formal computer language, this new technology will have a major impact on our interactions with computers.  Advanced search engines are a good example to illustrate the advantages that NanoSyntax will provide.  With previous technology, search engines were based on menus and key words.  Using NanoSyntax, search engines will be able to receive real human language input and relate the ideas behind the key words, giving the system a better understanding of what the user actually needs, which allows for more accurate search results.  This technology will also allow for better user-interface systems on a website, enabling users to quickly find the contents of the site that they desire.  Automated customer-service programs can also be simplified, enhancing the interaction between callers and the programs, thereby making the calls more effective and less painful for users.  NanoSyntax will provide application developers with a new layer of computer language comprehension, increasing the possibilities for development in games, online environments, educational software, and much more.  With the bridging of this communication gap, the complexity of computer usage will be lessened, which will certainly attract many new users who were previously overwhelmed by our technologies.

 

Spoken and written language has been the defining characteristics of the higher learning of the human species.  Language has often been a barrier between different cultures and is the greatest barrier between humans and animals and machines.  The use of NLP will allow this barrier to be broken between humans and computers.  Improved communication between humans and computers create an increased comfort for computers to be “user friendly.”  The NanoSyntax software is the answer to difficult search engines and annoying automated systems, thus giving them the competitive advantage in this difficult market.  Linguistic Agents has created a solution for a problem that has existed for over 40 years and has created a new meaning for the term universal language.

 

References

 

Computers learn to parse natural human language.  Retrieved on March 28, 2007, from http://www.linuxdevices.com/news/NS6184618910.html

 

Introducing Natural Language Processing.  Retrieved on March 28, 2007, from http://nanosyntax.com/intor_to_nlp_jan_07.html

 

Nanosyntax Technologies.  Retrieved on March 28, 2007, from http://www.nanosyntax.com

 

Nanosyntax-The Magic That Makes It All Possible.  Retrieved on March 28, 2007, from http://www.linguisticagents.com/technology.html

 

Talking Naturally.  Retrieved on March 28, 2007, from http://www.tmcnet.com/scripts

 

Technology Allows Computers to Decipher Human Language-File Cluster.  Retrieved on March 28, 2007, from http://www.filecluster.com/news/.html

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Nanosyntax:  Natural Language Processing
Group 1

 

1. 

What is one thing that Nanosyntax will improve?

 

A.  The improvement  of the search engine results  

    

 

B.  It will not improve anything  

 

 

C.  Will improve the quality of the computer  

 

 

D.  None of the above  

 

 

 

 

2. 

What is the technology that translates normative human language into a form of computer language?

 

A.  Linguistic Agent  

    

 

B.  Nanosyntax  

 

 

C.  Natural Language Processing  

 

 

D.  Theoretical Linguistic 

   

 

 

 

 

1. 3.3. 2.3.

How many different types of understanding can be spoken by humans and be broken down?

 

A.  One  

    

 

B.  Four  

 

 

C.  Two  

 

 

D  Three.  

   

 

 

 

 

4. 

What technologies was used on the old Natural Language Processing

 

A.  Natural Language Analysis  

    

 

B.  Language Decoding  

 

 

C.  Natural Language Software  

 

 

D  Statistical Models.  

   

 

 

 

 

5. 

How long has it been since any upgrades have been made to the NLP system?

 

A.  50 Years  

    

 

B.  2 decades  

 

 

C.  15 years  

 

 

D.  4 decades  

   

 

 

 

 

6. 

What is the companies name responsible for the Nanosyntax?

 

A.  Ninosyntax  

    

 

B.  Linguistic Agents  

 

 

C.  NLP  

 

 

D.  Inux  

   

 

 

 

 

7. 

What is NLP?

 

A.  Natural Learning Prototype  

    

 

B.  Natural Linguistic Processing  

 

 

C.  Natural Language Processing  

 

 

D.  Natural Language Prototype