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Argo: an integrative, interactive, text mining-based workbench supporting curation

机译：Argo：基于文本挖掘的集成，交互式，支持策划的工作台

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Curation of biomedical literature is often supported by the automatic analysis of textual content that generally involves a sequence of individual processing components. Text mining (TM) has been used to enhance the process of manual biocuration, but has been focused on specific databases and tasks rather than an environment integrating TM tools into the curation pipeline, catering for a variety of tasks, types of information and applications. Processing components usually come from different sources and often lack interoperability. The well established Unstructured Information Management Architecture is a framework that addresses interoperability by defining common data structures and interfaces. However, most of the efforts are targeted towards software developers and are not suitable for curators, or are otherwise inconvenient to use on a higher level of abstraction. To overcome these issues we introduce Argo, an interoperable, integrative, interactive and collaborative system for text analysis with a convenient graphic user interface to ease the development of processing workflows and boost productivity in labour-intensive manual curation. Robust, scalable text analytics follow a modular approach, adopting component modules for distinct levels of text analysis. The user interface is available entirely through a web browser that saves the user from going through often complicated and platform-dependent installation procedures. Argo comes with a predefined set of processing components commonly used in text analysis, while giving the users the ability to deposit their own components. The system accommodates various areas and levels of user expertise, from TM and computational linguistics to ontology-based curation. One of the key functionalities of Argo is its ability to seamlessly incorporate user-interactive components, such as manual annotation editors, into otherwise completely automatic pipelines. As a use case, we demonstrate the functionality of an in-built manual annotation editor that is well suited for in-text corpus annotation tasks. Database URL: http://www.nactem.ac.uk/Argo
机译：文本内容的自动分析通常支持生物医学文献的处理，而文本内容的自动分析通常涉及一系列单独的处理组件。文本挖掘（TM）已被用于增强手动生物固化的过程，但一直专注于特定的数据库和任务，而不是将TM工具集成到策展管道中的环境，以适应各种任务，信息类型和应用程序。处理组件通常来自不同的来源，并且通常缺乏互操作性。完善的非结构化信息管理体系结构是通过定义通用数据结构和接口来解决互操作性的框架。但是，大多数工作都是针对软件开发人员的，不适合策展人，否则，在较高的抽象级别上使用不方便。为了克服这些问题，我们引入了Argo，这是一个用于文本分析的可互操作，集成，交互式和协作的系统，具有便捷的图形用户界面，可简化处理工作流程的开发并提高劳动密集型手动管理的生产率。健壮，可扩展的文本分析遵循模块化方法，采用组件模块进行不同级别的文本分析。用户界面完全可以通过Web浏览器使用，从而使用户不必执行通常复杂且依赖于平台的安装过程。 Argo带有一组预定义的处理组件，这些组件通常用于文本分析，同时使用户能够存放自己的组件。该系统可容纳用户领域的各个领域和级别，从TM和计算语言学到基于本体的策展。 Argo的主要功能之一是能够将用户交互组件（例如手动注释编辑器）无缝地集成到其他自动化流程中。作为一个用例，我们演示了内置手动注释编辑器的功能，该编辑器非常适合文本语料库注释任务。数据库网址：http：//www.nactem.ac.uk/Argo

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