Much progress has been made in the provision of reusable data resources for Natural Language Engineering, such as grammars, lexicons, thesauruscs. Although a number of projects have addressed the provision of reusable algorithmic resources (or 'tools'), takeup of these resources has been relatively slow. This paper describes GATE, a General Architecture for Text Engineering, which is a freely-available system designed to help alleviate the problem.

/pdf/gate-a-general-architecture-for-text-engineering-45oblt9d6u.pdf

GATE - a General Architecture for Text Engineering

This paper presents the design, implementation and evaluation of GATE, a General Architecture for Text Engineering.GATE lies at the intersection of human language computation and software engineering, and constitutes aninfrastructural system supporting research and development of languageprocessing software.

GATE, a General Architecture for Text Engineering

Modular visualization environments utilizing a data-flow execution model have become quite popular in recent years, especially those that incorporate visual programming tools. However, simplistic implementations of such an execution model are quite limited when applied to problems of realistic complexity, which negate the intuitive advantage of data-flow systems. This situation can be resolved by extending the execution model to incorporate a more complete and efficient programming infrastructure while still preserving the virtues of "pure data-flow". This approach has been used for the implementation of a general-purpose software package, IBM Visualization Data Explorer.

An extended data-flow architecture for data analysis and visualization

General-purpose robots can perform a range of useful tasks in human environments; however, programming them to robustly function in all possible environments that they might encounter is unfeasible. Instead, our research aims to develop robots that can be programmed by its end-users in their context of use, so that the robot needs to robustly function in only one particular environment. This requires intuitive ways in which end-users can program their robot. To that end, this paper contributes a flow-based visual programming language, called RoboFlow, that allows programming of generalizable mobile manipulation tasks. RoboFlow is designed to (i) ensure a robust low-level implementation of program procedures on a mobile manipulator, and (ii) restrict the high-level programming as much as possible to avoid user errors while enabling expressive programs that involve branching, looping, and nesting. We present an implementation of RoboFlow on a PR2 mobile manipulator and demonstrate the generalizability and error handling properties of RoboFlow programs on everyday mobile manipulation tasks in human environments.

/pdf/roboflow-a-flow-based-visual-programming-language-for-mobile-1q01bnz4ox.pdf

RoboFlow: A flow-based visual programming language for mobile manipulation tasks

The directness, immediacy, and simplicity of visual programming languages are appealing. The question is, can VPLs be effectively applied to large scale programming problems while retaining these characteristics. In scaling up, the problem is how to expand applicability without sacrificing the goals of better logic expression and understanding. From a size standpoint, scaling up refers to the programmer's ability to apply VPLs in larger programs. Such programs range from those requiring several days' work by a single programmer to programs requiring months of work, large programming teams, and large data structures. From a problem domain standpoint, scaling up refers to suitability for many kinds of problems. These range from visual application domains-such as user interface design or scientific visualization-to general purpose programming in such diverse areas as financial planning, simulations, and real time applications with explicit timing requirements. To illustrate the scaling up problem, we discuss nine major subproblems and describe emerging solutions from existing VPL systems. First, we examine representation issues, including static representation, screen real estate, and documentation. Next, we examine programming language issues-procedural abstraction, interactive visual data abstraction, type checking, persistence, and efficiency. Finally, we look at issues beyond the coding process. >

Scaling up visual programming languages

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Scaling up visual programming languages