Aperture is a Java framework for extracting and querying full-text content and metadata from various information systems. It could crawl and extract information from File system, Websites, Mail boxes and Mail servers. It supports various file formats like Office, PDF, Zip and lot more. Metadata information is extracted from image files. Aperture has a strong focus on semantics, metadata extracted could be mapped to predefined properties.

Aperture - Java framework for getting data and metadata

GATE excels at text analysis of all shapes and sizes. It provides support for diverse language processing tasks such as parsers, morphology, tagging, Information Retrieval tools, Information Extraction components for various languages, and many others. It provides support to measure, evaluate, model and persist the data structure. It could analyze text or speech. It has built-in support for machine learning and also adds support for different implementation of machine learning via plugin. 
 It has family of products: 
 GATE Developer: An integrated development environment for language processing components bundled with a very widely used Information Extraction system and a comprehensive set of other plugins. 
 
 GATE Teamware: A collaborative annotation environment for factory-style semantic annotation projects built around a workflow engine and a heavily-optimized backend service infrastructure. 

 GATE Embedded: An object library optimized for inclusion in diverse applications giving access to all the services used by GATE Developer and more.
 <img src="/AppImages/Article/gate_img1.jpg" alt="" class="float-center">

GATE excels at text analysis of all shapes and sizes. It provides support for diverse language processing tasks such as parsers, morphology, tagging, Information Retrieval tools, Information Extraction components for various languages, and many others. It provides support to measure, evaluate, model and persist the data structure. It could analyze text or speech. It has built-in support for machine learning and also adds support for different implementation of machine learning via plugin.

Gate - General Architecture for Text Engineering

SMILA is an extensible framework for building search solutions to access unstructured information in the enterprise. Besides providing essential infrastructure components and services, SMILA also delivers ready-to-use add-on components, like connectors to most relevant data sources. Using the framework as their basis will enable developers to concentrate on the creation of higher value solutions, like semantic driven applications etc. It has a crawler / agent, which pushes the data. The data is then	processed by various filters. BPEL workflows could be created using its WorkerManager. The pipeline could be well managed by this workflow engine. 
 <img src="/AppImages/Article/smila_img1.jpg" alt="" class="float-center">

SMILA is an extensible framework for building search solutions to access unstructured information in the enterprise. Besides providing essential infrastructure components and services, SMILA also delivers ready-to-use add-on components, like connectors to most relevant data sources. Using the framework as their basis will enable developers to concentrate on the creation of higher value solutions, like semantic driven applications etc.

SMILA - Unified information access architecture

UIMA analyzes large volumes of unstructured information in order to discover knowledge that is relevant to an end user. It is a framework with different set of components. The components include Language Identification, Language specific segmentation, Sentence boundary detection, Entity detection (person/place names) etc. The framework manages these components and the data flows between them. It could detects entities like email addresses, URLs, phone numbers, zip codes or any other entity based on regular expressions.
 <img src="/AppImages/Article/uima-img1.jpg" alt="" class="float-center">

UIMA analyzes large volumes of unstructured information in order to discover knowledge that is relevant to an end user. It is a framework with different set of components. The components include Language Identification, Language specific segmentation, Sentence boundary detection, Entity detection (person/place names) etc. The framework manages these components and the data flows between them.

UIMA - Unstructured information management architecture

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Aperture - Java framework for getting data and metadata

Gate - General Architecture for Text Engineering

SMILA - Unified information access architecture

UIMA - Unstructured information management architecture

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Aperture - Java framework for getting data and metadata

Gate - General Architecture for Text Engineering

SMILA - Unified information access architecture

UIMA - Unstructured information management architecture

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