AR·Semantics for MarkLogic Server
MarkLogic Server is an unstructured database engine. It can’t be beat for processing huge amounts of data with all levels of structure. Likewise, XML is tailor-made for dealing with hierarchical information that you will find in taxonomies. In fact, it is quite intuitive to work with taxonomy data in a MarkLogic database, since XML and Taxonomies work together so naturally.
MarkLogic and Applied Relevance are natural companions. AR Semantics makes it easy to manage and apply taxonomies to documents, and MarkLogic Server makes it possible to process big data with unmatched performance and power.
Why MarkLogic Server?
MarkLogic Server is a very powerful database and unstructured text engine. Applied Relevance leverages this power to build a highly efficient and fast classification server.
MarkLogic Server has unique features which makes it well-suited to automatic classification. For example, the MarkLogic engine supports field-level updating. This means that documents can be annotated very quickly without reindexing.
AR·Semantics plus MarkLogic server is an unbeatable solution for finding what you know and discovering what you don’t know.
Publishing, Finance, Government and then some
The traditional market strength of MarkLogic for publishing, the financial sector and government applications also happend to be areas where agile taxonomies can really help.
As publishing grows into its new electronic role, organizing and drilling-down through massive amounts of high-value unstructured information is paramount to success in the new world. The three pillars of AR·Semantics: taxonomy management, auto-tagging and faceted navigation are all essential elements of modern electronic publishing.
Taxonomies act as data models for unstructured information. The publishing industry tends to have a lot of semi-structured information. While the text of an article or chapter may be mostly unstructured, there is a lot of structurehiddeninside typical prose. You just need to know where to look. That’s where taxonomies come in handy.
Tagging documents with metadata is a great way to make it findable. Web search engines use the built-in metadata of the web (links, domains, HTML tags and user behavior) to make searching with Google and Bing very effective. Unfortunately, your intranet or even your content management system does not have the same kinds of information that makes “I feel lucky” actually work. Even worse, nobody likes to manually tag documents. It is annoying.
AR·Semantics auto-tagging turns your taxonomies into tags by automatically adding metadata to documents at check-in time or when crawling for search. Since the metadata is already hidden inside your documents, no user has to try to think, “what did I just spend 8 hours writing so I can enter the key points into this stupid keywords field?”.