Posts Tagged ‘machine learning’

Building Machine Learning Tools to Mine Unstructured Text

Friday, February 17th, 2012

This presentation describes how to build tools to find the meaning of unstructured text using machine generated knowledge representation graphs using NLP and ai-one’s Topic-Mapper API.
The prototype solution, called ai-Browser, is a generalized approach that can solve the following types of use cases:
  • Sentiment analysis of social media feeds
  • Evaluating electronic medical records for clinical decision support systems
  • Comparing news feeds
  • Electronic discovery for legal purposes
  • Automatically tagging documents
  • Building intelligent search agents
The source code for ai-Browser is available to developers to customize to meet specific requirements. For example:
  • Healthcare providers can use ai-Browser to analyze medical records by using ontologies and medical lexicons.
  • Social media marketing agencies can use ai-Browser to create personal profiles of customers by reading social media feeds.
  • Researchers can use ai-Browser to mine PubMed and other repositories.
Our goal is to get the source code and the API into the hands of commercial companies who want to tailor the application to solve specific problems.
Click here to download the presentation from SlideShare:
View more presentations from ai-one

Partnership to Create New Social Media Intelligence Tools

Thursday, February 16th, 2012

New Partnership Targets Creation of Social Media Intelligence Tools

Press Release

Tweet log

New tools will enable machine learning of twitter feeds

La Jolla CA | Zurich | Berlin  February 16 2012 – ai-one inc. and Gnostech Inc. announced a partnership today to build new machine learning applications for the US government and military. The deal brings together two small firms that are well known for developing cutting-edge technologies. Gnostech specializes in simulation and modeling, Command Control Communications Computers and Intelligence Surveillance and Reconnaissance (C4ISR) systems and security engineering and Information Assurance (IA) applications. The partnership with ai-one provides Gnostech with access to technology that enables computers to learn the meaning and context of data in a way that is similar to humans. Called “biologically inspired intelligence” the technology is a new form of machine learning that is particularly useful for understanding complex, unstructured information – such as conversations in social media.

In the past month, the US government has issued six requests for companies to create solutions to help better understand TwitterFacebook and other social media sources. These broad area announcements (BAAs) are formal requests from the Government to invite companies to provide turn-key solutions. With more than 800 million people actively using Facebook and more than 100 million Twitter users, governments and intelligence agencies know that they need better ways to mine this data to get real-time information to protect national security.“

We now have more than 40 partners worldwide that are experimenting with our technology – but only 3 that specialize in US government applications,” said Tom Marsh, President of ai-one. “Gnostech is local, technically driven and well positioned to develop rapid prototypes using our technology.”

About Gnostech, Since 1981, Gnostech has provided technical and engineering services to the Department of Defense (DOD) and Department of Homeland Security (DHS). Gnostech has a proven reputation for engineering efficiency, systems innovation, and dedicated customer service.

Gnostech Inc. began as an engineering and consulting company in Warminster, PA with expertise in GPS simulations and software, initially supporting the US Navy at the Naval Air Development Center (NADC) in Warminster, PA. Today, Gnostech has grown from a few people to about 50 employees with a satellite office in San Diego, CA and engineering support staff in Norfolk, VA, Morristown, NJ and Philadelphia, PA. Gnostech’s technical expertise expands upon our GPS experience and extends into Mission Planning, Network Engineering, Information Assurance and Security Engineering.  www.gnostech.com

About ai-one inc., ai-one provides an “API for building learning machines”.  Based in San Diego, Zurich and Berlin, ai-one’s software technology is an adaptive holosemantic data space with semiotic capabilities (“biologically inspired intelligence”).  The Topic-Mapper™ SDK for text enables developers to create intelligent applications that deliver better sense-making capabilities for semantic discovery, lightweight ontologies, knowledge collaboration, sentiment analysis, artificial intelligence and data mining.  www.ai-one.com

Mining Unstructured Text: A new machine learning approach

Monday, February 13th, 2012

We believe we have found a new approach to apply a new general purpose machine learning technology to solve domain-specific problems by mining unstructured text. The solution addresses fundamental problems in knowledge management:

ai-browser is a tool for mining unstructured textHow to find information that is difficult to describe?

For example, you want to find a match between two people to fill an empty job position. What attributes do you use to represent a complex subject (like a person) to find the best fit?

What if the single best answer is hidden within a vast amount of unstructured text?

Let’s say you want to repurpose a drug – such as using the side-effect of a chemical to treat a disease using a newly discovered metabolic pathway. How would you search through the 21+ million research articles in PubMed to find the best match from more than 2,000+ known drug compounds?

What if the textual information is constantly changing?

What if you want to provide personalized marketing to a person based on what they are saying on Facebook, Twitter or LinkedIn?  To do this, you must understand the meaning of what they are saying. The most accurate approach is to have people read and interpret the conversations because we are fantastic at understanding the complexity of language. But to do this with a computer requires a different approach: Machines must learn like humans. They must understand how meaning evolves in a conversation, how to disambiguate, how to detect the single most important concepts, etc.

Big Data Means Big Opportunity

These are classic “Big Data” problems – and they are rampant. Finding a solution would change everything; from how we discover new drugs to what social media would tell us about ourselves.

There have been many attempts to find ways for machines to learn like a human. Artificial intelligence has made bold promises that have been consistently broken for more than 50 years. Yet, we still don’t have a universal approach for machines to learn and understand language like a human.

Growth of Websites

Now, more than ever, we need to find a new approach to mine unstructured text. As of February 2012, it is estimated that the Internet has more than 614 million websites. More than 1.8 zettabytes of information was created in 2011 – more than much of it unstructured text from our comments on websites, news articles, social media feeds… just about anything where people are communicating with language rather than numbers.

Unstructured text can’t be processed like structured data. Rather it requires an approach that enables knowledge representation in a form that can be processed by machines.

Knowledge representation is a rich field and there has been tremendous effort and innovation – too many to describe here. However, we still live in a world where the overwhelming majority of people (including almost every CIO, developer and consumer) CANNOT find the information they seek with a simple query. Rather, the domain of data mining text analytics is dominated by specialists who use tools that are very difficult to learn and very expensive to deploy (because they require highly skilled programmers).

We set out to create a new toolset that would be easy to use for almost any programmer to build data mining tools for unstructured text.

ai-browser: A prototype for human-machine collaboration

For the past several months, we have been working on a new approach for text analytics and data mining. The idea is to create a tool that enables human-machine collaboration to quickly mine unstructured data to find the single best answer.

We now have a working prototype, called ai-browser, that solves knowledge management and data mining problems involving unstructured text. It combines natural language processing (NLP) and pattern recognition technologies to generate a precise knowledge representation graph.  Our team selected OpenNLP because it is open-source, easy to use and customize. We used the Topic-Mapper API to detect patterns within the text after it was pre-processed to isolate parts of speech. The system also allows users to use ontologies and/or reference documents to sharpen the results. The output is a graph that can be used in a number of ways with 3rd party products, such as:

  • Submission to search appliances like Google, Bing, Lucene, etc.
  • Analysis with modelling tools like Cytoscape, MATlab, SAS, etc.
  • Enterprise systems for reporting, knowledge management and/or decision support

This graph makes it easy to ask questions like, “Find me something like _______!” and get a very tightly clustered group of results – rather than millions of hits.

Even more impressive, ai-browser’s graph is a powerful tool that can be applied to a wide range of applications, such as:

  • Healthcare – clinical decision support systems to enable physicians to make better decisions by understanding all the relevant information held in electronic medical records (EMRs) – including emerging trends and relationships within the patient population.
  • Social media – detecting and tracking sentiments in conversations over time (such as Twitter) to understand how brands are perceived by customers.
  • Innovation management – discovering the relationships of information across disciplines to foster more productive collaboration and interdisciplinary discoveries.
  • Information comparison and confirmation – determine the similarities and differences between two different sources of content.
  • Human resources – sourcing and placement of the best candidate for a job based on previous work experience.

The intent of the ai-browser design is to provide a starting point for developers to build solutions to meet the specific needs of enterprise customers. For example, modifying the system enables solutions to the following use cases:

  • Help a physician determine if additional tests are necessary to confirm a diagnosis.
  • Determine how perceptions about a brand are change through conversations on Twitter.
  • Find new uses for a drug by reviewing clinical studies published on PubMed and determining if there are relevant patent filings.
  • Identify stock market trading opportunities by comparing news feeds and SEC filings on a particular company or industry.
  • Finding the best person for a job by searching the internet for someone that is “just like person who has this job last year.”

Enterprise Data Mining: A far easier, lower cost approach.

Unlike other data mining approaches, ai-browser learns the meaning of documents by generating a lightweight ontology – a dynamic file that describes every relationship between every data element. It detects keywords and their association words which provide context. The combination of a keyword and all the association words can be thought of as a coordinate (x,y0->T) where x is the keyword and y0->T is the series of association words for that specific keyword. The collection of these coordinates creates a topology for the document: G(V,E) where G is graph and V is the set of vertices (or nodes) represented by each keyword and E is the edge represented by the associations to the keyword.

ai-fingerprint of Fox News Article

We call this graph the “ai-fingerprint.” It is a lossless knowledge representation model. It captures the meaning of the document by showing the context of words and the clustering of concepts. It is lossless because it captures every relationship in a directed graph – thereby revealing the significance of a word that may only appear once yet is central to the meaning of a large, complex textual data set.

ai-browser expresses ai-fingerprints uses the XGMML format in REST. This enables it to accommodate dynamic data, so it can change as the underlying text changes (such as in text from social media feeds).

Contact Olin Hyde to schedule a demo of ai-Browser. The source code is available to programmers to license and modify to solve specific problems.

ai-one Use Case: Enhance OCR of Credit Card Receipts using Machine Learning API

Wednesday, December 14th, 2011

OCR Correction using ai-one machine learning API


Use Case Summary:

The BON Matcher is an ai-one implementation enabling a leading swiss retail store to analyze all scanned credit card receipts.

After the scan process, all credit card receipts are analyzed and matched against patterns using a-one’s API.

Our solution corrects the errors of the optical character recognition (OCR) system when it fails to recognize 100% of the elements.

This was an early validation of our technology. It  affirmed ai-one’s superiority over alternative artificial intelligence-based solutions as a much faster, better quality, and less expensive solution. The retail chain saved substantial operating costs by automating this process and was able to reduce its workforce by 15 people.

The project was finished after 3 months of development time and is still being used for more than 80 stores.

The feature of the technology used in this application is commonly used in document archiving systems where users need to search for documents that have been scanned with many character errors.

Benefits:

  • Improved OCR performance from 80% to 98% in less than a week after implementation.
  • Enhancing OCR recognition in a separate, low-cost post processing process
  • Faster data availability
  • Additional fraud detection possibilities

Deployment:

Customize software development

Status:

Solution in place. Successful since 2006 launch.

Partner:

Swiss Data Safe AG

Application areas:

  • OCR recognition
  • Numerical series matching
  • Data management / Archiving

Target Industries:

  • Information management
  • Retail

 

OCR Correction Workflow Using Machine Learning API

 


Lead, Follow or Fail: AI and Your Business in 2012

Thursday, October 20th, 2011

Press Release

San Diego CA | October 20, 2011 – Did you miss the wave? Artificial intelligence is transforming entire industries by finding value in big, complex data.

The San Diego Online Society (SANDIOS) will host a public seminar on Thursday November 17 on how artificial intelligence (AI) is being used by leading edge companies around the world.

Recent advances in AI technology make it easy to build machines that can learn like humans. Now almost any programmer can build systems like Apple’s SIRI and IBM Watson by combining off-the-shelf technologies. A leading vendor of machine learning technology, ai-one, will present case studies from a wide range of customers. The seminar will focus on showing practical ways businesses can use AI.

Questions that will be addressed: 

  • What is AI & why everything you think you know about AI has changed
  • Business uses for ai-one technology
  • Demo of a cutting edge AI application
  • AI incubation models
  • How to succeed with building an AI business
  • AI Product strategy

The event will be hosted by Jones Day which specializes in intellectual property and business law.

Tickets available online at:   http://sandios-11-2011.eventbrite.com/

About ai-one inc., ai-one provides an “API for building learning machines”.  Based inSan Diego,Zurich andBerlin, ai-one’s software technology is an adaptive holosemantic data space with semiotic capabilities (“biologically inspired intelligence”).  The Topic-Mapper™ SDK for text enables developers to create artificial intelligence applications for semantic discovery, knowledge collaboration, sentiment analysis, and data mining.

Contact: Olin Hyde, Ph: 1-858-381-5897, email: oh@ai-one.com, web: www.ai-one.com

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Machines can learn.

Saturday, September 10th, 2011

Check out our newest video (3 min 34 sec). Machines can learn.

 

Machines can learn.

Machines can learn.

 

 

 

 

Machine Learning Makes Twitter Smarter in Portuguese

Thursday, July 14th, 2011

Press Release

Brazilian Arquiware signs deal to use new machine learning SDK to enhance sentiment analysis of social media networks.

La Jolla CA | São Paulo – Marketing consumer products in Brazil is about to get a lot easier thanks to a small, innovative software company. Arquiware is combining artificial intelligence with natural language processing to enable companies to analyze feelings and opinions social media networks. They are among the first in the world to apply techniques to create tools that enable companies to understand the sentiments of customers.

“Many multi-nationals come to Brazil then realize that it takes more than understanding Portuguese to understand how a brand interacts with consumers.” said Luis Lima, President of Arquiware, “In fact, the diversity of Brazil makes it almost impossible to understand our market unless you use sophisticated tools to extract the true meaning of what people are saying about you.”

Arquiware will add ai-one’s Topic-Mapper SDK to build artificial intelligence into two existing products. SentimentWare and TopicExtractWare analyze text data from social media networks and news feeds. The new capability gives Arquiware clients the ability to understand how any given news event will impact the perception of a brand.

ai-one’s technology is used by telecom companies, security and law enforcement agencies to enable computers to read text in a similar manner to humans. “We are thrilled that Arquiware will apply our technology to social media sentiment analysis. They are ahead of the efforts I have seen in Silicon Valley,” commented Olin Hyde, VP of Business Development for ai-one.

About Arquiware DSC (Brazil), Arquiware is one of Brazil’s leading software companies specializing in application development using natural language processing (NLP) and text mining. Arquiware builds custom applications for numerous enterprise clients and sells commercial off-the-shelf products for sentiment analysis and text extraction. SentimentWare provides sentiment analysis of social networks using the Radian6 API. TopicExtractWare is a SaaS that summarizes the meaning of any corpus of text by distilling information into tag clouds. Visit Arquiware’s free sentiment analysis of Twitter feeds to determine the best samba school in Carnival.

Contact:  Luis Lima Phone +55-11-233-82742, email: lglima (at) arquiware.com.br web: http://www.arquiware.com.br

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AI Goes to Wall Street: Trading Platforms Get Smarter

Thursday, June 30th, 2011

Press Release

It is no secret that for many years global banks have used artificial intelligence to make better trades. Now that technology might be coming to your local independent investment advisory service.

Caapi Technologies just announced that it signed a deal to use artificial intelligence technology to build custom trading systems for small to mid-size investment firms. Caapi will build applications with software development kits (SDKs) from ai-one that enable computers to understand human language to find undervalued stocks, bonds and derivatives.

The partnership makes Caapi one of the first consulting firms to use ai-one’s machine learning technology to build trading algorithms and platforms for traders, banks and hedge funds.

Building custom trading algorithms is a huge industry propelled by the success of high-frequency trading across global markets. Originally, these algorithms were designed to find and exploit pricing differences between stocks, commodities and derivatives. Now trading algorithms are so widespread and so sophisticated that they have completely reshaped markets to the point where pricing is often driven more by speculation than it is by the underlying value of the asset class.

The challenge now is to find underpriced opportunities that generate returns based on actual performance rather than market volatility. This requires that investors sort through vast amounts of unstructured data to find undervalued assets before they are identified by the rest of the market. Often this means reading text that can’t be processed by search engines like Google. Traditional algorithmic approaches, such as Google’s, fail as they only know what they are programmed to know or programmed to find. They miss finding unexpected results that don’t fit into an equation.

ai-one’s technology is described as “biologically inspired intelligence.” It is modeled after the human brain and does not depend on algorithms. Rather, it automatically sees the inherent patterns within data and forms associations between each data element. This enables machines to learn without any human intervention. More importantly, it enables people to ask the questions they wouldn’t normally know to ask.

The CEO of Caapi, Mr. Moris Oz, sees machine learning as the key to discovering hidden investment opportunities. “a-one’s technology enables us to build semantic associative search engines for our clients that understand how the price of any given investment is related to the unstructured data found on the internet.”

Caapi’s approach is to combine proven techniques using sophisticated algorithms with machine learning that understands words.  “Language is not math,” adds Olin Hyde, VP of Business Development at ai-one. “Algorithms are fantastic at processing structured data. But human behaviors and communications are inherently unstructured and complex. We learn through words not equations. So why not enable computers to do the same?”

According to Moris Oz, CEO of Caapi, “ai-one’s SDK for machine learning could be the answer for understanding and correlating soft data driving price moves in the markets.  I’m looking forward to applying this to new applications.” The market will soon tell if it works or not.

About Caapi Technologies, Founded by Moris Oz, the company offers consulting, system engineering, Algo trading machines and rigid body physics simulations. They design, program and deliver complex algorithmic and automated trading platforms. Caapi’s expertise spans the most common technology platforms such as Java, .NET, GWT, Flex, PHP, CSS, JS, Facebook SDK etc., for building scalable, feature-rich Web applications. Based in Israel, Caapi services encompass project management, software design, software development, quality assurance, documentation, and technical support.

For more information see http://www.caapitech.com

Contact Moris Oz, Ph +972-9-8656875 email moris@caapitech.com

About ai-one inc., ai-one provides an “API for building learning machines”.  Based in San Diego, Zurich and Berlin, ai-one’s software technology is an adaptive holosemantic data space with semiotic capabilities (“biologically inspired intelligence”).  The Topic-Mapper™ SDK for text enables developers to create intelligent applications that deliver better sense-making capabilities for semantic discovery, lightweight ontologies, knowledge collaboration, sentiment analysis, artificial intelligence and data mining.

For more information see http://www.ai-one.com

Contact: Olin Hyde, Ph: 1-858-531-0674, email: oh@ai-one.com, web: www.ai-one.com