AMB New Generation Data Empowerment Releases Self-Learning Enrichment Search/Integration Technologies

Leverages Access to Portals, Social Networks, Search/Content Indices, Data Warehouses and Legacy Systems

 

AMB, a premier provider of data governance solutions, including on-demand profiling and quality remediation, MDM and an appliance based approach to information governance, announces its first generation release of AMB/Content. Through self-learning categorized search tables, web services enabled, this product deploys domain expertise across the enterprise and can be easily integrated to leverage existing investments in common application systems. AMB/Content will:

 

·         Enhance the quality of domain content captured from searching portals, social media,

web 2.0 data, and conventional information sources

·         Automatically capture and activate logical, fuzzy, and custom related data values to create a continually improving knowledge store that will maximize the value of the next search results

·         Real time enrichment services that can be performed from legacy web-enabled applications or as a data quality workbench for content management

 

This content, once enhanced, will improve the consumer experience for:

·         Web-based shopping and loyalty sites

·         Behavioral targeting

·         Data intensive social media information collection

·         Intelligent interfaces used to modernize legacy systems

 

How many times have you gone to Google, Yahoo, Bing or some other search engine or your Company’s internal or vendor driven Content indexes looking for something rather specific, only to receive thousands of unnecessary hits or not find the answer even though it’s out there? It’s not always the way you searched that’s the problem. Too often it is because the indexes used during the search have not been enriched.

 

How AMB has managed to complete what others are just conceptualizing

 

The key to AMB’s success is its Self-Learning-Lexicon technology and AMB-Data Profiling, Quality, Governance Suite, as companies or individuals establish their searching criteria to analyze and bring to the surface their intended/desired results. These are only as successful as their knowledge of specific areas of expertise. AMB utilizes the ongoing knowledge of all that participate in this searching experience and retain the desired knowledge and expertise of the collective searchers and expand the AMB-Standardize tables by adding to this table the successful search results that resulted in the desired information returned. As AMB’s Standardize tables grow through this self learning methodology all subsequent search activities deliver much more accurate and valuable information to those that depend on these results to be accurate.

 

Integrating Portals and Data Warehouses

 

One of the key uses of our AMB/Content offering is facilitating the seamless integration of document centric knowledge bases, such as portals, web sites and social media with data warehouses. This is accomplished by using our advanced content enhancement capabilities to ensure the alignment of information used to navigate knowledge management systems (portals, etc.) with business

intelligence data stores.  Once integrated, this information can be leveraged in ways not easily accomplished today, for critical applications that many find daunting today.  Those that require near real time detection, such as homeland security, anti-money laundering and other time sensitive applications are not out of reach, since the AMB/Content product is designed to be used as a real time component of your information arsenal and can be integrated as close to transactions as you wish.

 

It’s the data that creates content

When we addressed using profiling and data governance techniques against unstructured content, we realized that there were significant benefits to be realized were something big here.  The ability to keep online business information and web content accurate is difficult using the typical content indexing processes employed today.  Furthermore, the amount of information processed during a search request is too large to enhance the results during the building process Biased search techniques will skip content for the sake of speed.  The optimum solution is to enhance the search index, either as a batch process or as an appliance that can be used in conjunction with content index creation.  This is what AMB has built.

 

Steve Meister, Chief Technology Officer of AMB says “By making the lexicon self-learning, AMB has removed the primary efficiency bottleneck to enrichment: real-time indexing of unstructured content that learns as it indexes content.  “The result is a facility that automatically persists, continually applying rules to new content, thus creating the richest index possible.  By making the lexicon self-learning, AMB/Content is able to further minimize false positives within the search experience as well as delivering links to content that would otherwise have been missed.”

 

Mark Albala, President of InfoSight Partners, LLC and an industry expert stated, “Portals and web sites grew up with different teams and rules than did data warehouses, and that causes a conformity issue.   Add to that the fact that most web sites form their indices on keywords identified by the author through an SEO process, and it really comes down to the fact that the indices created for content management are woefully poor for search, because the index used for content search is so flawed.  Call it the capabilities of technology when these things were devised, or something else, but a small elevation in the quality of the search index makes a huge impact on the search experience, which is of tremendous value to web buying portals, loyalty programs and other applications that count on search to quickly find information, like AML and homeland security.“

 

Mr. Albala adds “This really is a big deal, the fact that AMB can act as a bolt on appliance to elevate the quality of the index is huge because it circumvents the need for a rewrite of something architected several years ago.  The fact that it is service based means that it can serve as a real time appliance.”

 

Why our self-learning process is key

When AMB/Content is used in real time for content indexing enrichment, the one bottleneck to enrichment tends to be new lexicon entries that have not been indexed. We approached this problem by making the lexicon self- learning.  The result is a facility that automatically persists, continually applying rules to new content, thus creating the richest index possible.  By making the lexicon self-learning, AMB/Content is able to minimize false positives from the search experience.