Senior Director of Sales
A fundamental challenge exists in today’s NLP-based text analytics solutions; the volume of dynamic data is exploding and there are not enough subject matter experts available to map out the relationships between concepts.
Many aspects of advanced text mining capabilities rely on the existence or creation of ontologies, semantic rules, and templates to:
- Resolve ambiguity to determine the right meaning
- Determine synonym relationships
- Identify and categorize entities, actions and events
Creating deep ontologies and semantic rules using traditional text analytic approaches (e.g. CRM, genomics, security intelligence) is a manual process. At times this is the preferred approach, because the relationships need to be mapped for a specific policy (e.g. practice systems for hospitals or answers to a support question).
The challenge for enterprises today is the majority of their data is unstructured and dynamically changing, making it difficult to surface insights and take action upon it in real-time. The cost of manually building an ontology and the lack of skilled subject matter experts make it unlikely that the enterprise ever adequately resources this activity. The rapid growth of dynamic and real-time data feeds across multiple internal and external sources, vital to business intelligence, exacerbates the difficulty of extracting true meaning from unstructured text data.
Atigeo’s xPatterns platform automates the creation and dynamic maintenance of semantic ontologies. xPatterns uses a neural network to model associations between concepts. It represents “IsAssociatedWith” relationships for domains, derived simply from reading and reviewing large bodies of unstructured text information about the domain that can be streamed to the system in real-time. The technology can be leveraged to determine indirect semantic relationships between queried concepts, and to facilitate understanding of the relevance of a specific document to a specific concept. It can dynamically extract key concepts from any viewed document and surface documents that are more closely related to it. This allows users to traverse and assimilate bodies of content in ways similar to how the human mind organizes information. This can allow a user to quickly learn about a new topic and make fact based decisions.
Moreover, it is also possible semantically index a user’s past queries and documents viewed to maintain unstructured semantic profile that can help personalize views, refine relevance or even proactively notify the user when related content gets added to the system.
xPatterns is a cloud based platform that can be easily integrated with existing enterprise applications and collect data from internal and external structured and unstructured sources. It can be used to augment existing business intelligence and text analytics solutions. The platform has been used to enhance search and discovery and speed assimilation of complex information. It can monitor trends in social media, match supplier capabilities to open RFPs, translate physician notes to ICD 10 codes and spot patterns of non-compliance or fraud, waste and abuse.
A picture or a demo is worth more than millions of random words. Go http://www.atigeo.com/videos/ today so see some of the ways we are connecting related concepts and delivering insights on large dynamic unstructured data sets.