PoolParty PowerTagging
Harness the power of automated semantic tagging to optimize search engines
PoolParty PowerTagging is a solution that comprises a rich set of semantic tools that focus on extraction and natural language processing of relevant terms, classification of documents and terms into a taxonomy, and concept mapping in graph-based search.
Using PoolParty Semantic Suite’s advanced auto classification and semantic concept tagging capabilities, organizations can create high-quality active metadata that improves search engines and builds recommender systems that deliver meaningful content.
Quick rundown of the benefits of PoolParty PowerTagging:
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- faster to find relevant documents and content
- more accurate filtering of non-relevant information
- consistent tagging based on controlled enterprise vocabularies
- automatic or semi-automatic content tagging based on text mining
- consistent tagging of multilingual content thanks to controlled vocabularies and business glossaries
- standards-based metadata of high quality
- tools that can interlink structured and unstructured information across data silos
Among the many benefits of PoolParty PowerTagging, the biggest takeaway is rich metadata, which directly influences the performance of search engines both internally in content management systems (CMS) and externally in customer platforms. With a semantic layer on top of your information architecture, you can analyze and create rich metadata automatically. Using powerful tagging processes to create metadata, you can bridge data silos, increase transparency to meet regulatory compliance and make business rules, and drastically improve user search experiences.
Tagging with PoolParty is not just about extracting important terms from text, but the ability to link data and content to a comprehensive knowledge graph, enriching it with rich contextual information.
PoolParty PowerTagging is a new-generation solution to auto tagging.
To make our solution the most comprehensive on the market, we have combined various semantic assets that tackle each of the limitations that other first-generation tagging solutions have.
Click on the boxes below to read more about the tools and try their specific demos.
Semantic Classifier
The Semantic Classifier uses knowledge graph and machine learning to precisely classify documents into their respective domains. In this case, news articles will be sorted into the domain (used by the Communications department and legal contracts will be sent to the Legal department. This product only requires a small training dataset to understand how to classify your documents automatically. The classified documents will be sent to their correct domains in order for the tags to be extracted correctly.
Entity Extractor
Extract terms, phrases, and entities from unstructured documents using text mining and natural language processing. You can have an extractor that is dedicated to each of your knowledge domains (Communications vs. Legal, from before) for precision and efficiency. The PoolParty Extractor extracts entities based on concepts instead of simple terms to make use of disambiguation of text in a taxonomy, synonyms, related concepts, alternative labels, etc.
Thesaurus Server
Tagged documents can be sorted into the different concept schemes of the taxonomy. The benefit to maintaining tags in a taxonomy is the consistency it provides through its hierarchical structure and controlled vocabularies. The taxonomy helps build a knowledge graph which then serves as a fundamental basis for enhancing search engines. Graph-based search engines and recommender systems can recall the concepts and their relationships defined in the annotated documents. As a result, the engines can suggest smarter results based on the user’s interactions with a platform and understanding of context and meaning.
What does a general PoolParty PowerTagging workflow look like?
Users have the option to use an automatic workflow or an expert-assisted workflow. The main difference between these two workflows is that the automatic version relies solely on the machines doing the work, whereas the expert-assisted workflow gives the user (in this case, the expert) the opportunity to review and approve tags before they are sent back to the CMS.
An automatic workflow comprises the following steps:
An expert-assisted workflow has the same main steps with one additional step. This step allows the expert to be kept in the loop so that tags can be refined if needed before they are saved and sent back to the CMS.
PoolParty PowerTagging Integrations.
PoolParty PowerTagging is equipped with ready-made integrations for some of the most widely used CMS on the market. You can check our PoolParty PowerTagging Integrations page to learn more about:
PoolParty for SharePoint improves SharePoint’s organization and search retrieval with automated semantic tags. Only a few minutes after setup, the software is able to seamlessly label SharePoint documents, recommend documents with related content and semantic search, and enrich SharePoint documents with relevant information from external sources.
PoolParty PowerTagging for Adobe Experience Manager enhances AEM’s tagging capabilities to gain more control over your tagging. This integration connects AEM to PoolParty’s taxonomy management tool, enriching AEM’s native tagging functionality and allowing you to manage your taxonomies centrally in an enterprise system.
PoolParty PowerTagging for Tridion enhances Tridion’s auto tagging capabilities and delivers an intelligent solution powered by semantic AI. As a result, help authors can automatically enrich content quickly and accurately with smart tagging which enhances semantic search in Tridion’s Dynamic Experience Delivery (DXD) platform.
Other Resources
Webinar: Autoclassification 101: Optimizing CMS Search with Automated Tagging.
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Named Entity Recognition Demo: automatically extract concepts and terms from text.
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Price and Product Overview: Get an overview of prices and functionalities.
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Interested in the PoolParty PowerTagging Solution? Download the PoolParty PowerTagging fact sheet to learn more.
