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        <title>CTAP: A Web-Based Tool Supporting Automatic Complexity Analysis</title>
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        <namePart type="given">Xiaobin</namePart>
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            <title>Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)</title>
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            <namePart type="given">Dominique</namePart>
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            <namePart type="given">Felice</namePart>
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    <abstract>Informed by research on readability and language acquisition, computational linguists have developed sophisticated tools for the analysis of linguistic complexity. While some tools are starting to become accessible on the web, there still is a disconnect between the features that can in principle be identified based on state-of-the-art computational linguistic analysis, and the analyses a second language acquisition researcher, teacher, or textbook writer can readily obtain and visualize for their own collection of texts. This short paper presents a web-based tool development that aims to meet this challenge. The Common Text Analysis Platform (CTAP) is designed to support fully configurable linguistic feature extraction for a wide range of complexity analyses. It features a user-friendly interface, modularized and reusable analysis component integration, and flexible corpus and feature management. Building on the Unstructured Information Management framework (UIMA), CTAP readily supports integration of state-of-the-art NLP and complexity feature extraction maintaining modularization and reusability. CTAP thereby aims at providing a common platform for complexity analysis, encouraging research collaboration and sharing of feature extraction components—to jointly advance the state-of-the-art in complexity analysis in a form that readily supports real-life use by ordinary users.</abstract>
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%0 Conference Proceedings
%T CTAP: A Web-Based Tool Supporting Automatic Complexity Analysis
%A Chen, Xiaobin
%A Meurers, Detmar
%Y Brunato, Dominique
%Y Dell’Orletta, Felice
%Y Venturi, Giulia
%Y François, Thomas
%Y Blache, Philippe
%S Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F chen-meurers-2016-ctap
%X Informed by research on readability and language acquisition, computational linguists have developed sophisticated tools for the analysis of linguistic complexity. While some tools are starting to become accessible on the web, there still is a disconnect between the features that can in principle be identified based on state-of-the-art computational linguistic analysis, and the analyses a second language acquisition researcher, teacher, or textbook writer can readily obtain and visualize for their own collection of texts. This short paper presents a web-based tool development that aims to meet this challenge. The Common Text Analysis Platform (CTAP) is designed to support fully configurable linguistic feature extraction for a wide range of complexity analyses. It features a user-friendly interface, modularized and reusable analysis component integration, and flexible corpus and feature management. Building on the Unstructured Information Management framework (UIMA), CTAP readily supports integration of state-of-the-art NLP and complexity feature extraction maintaining modularization and reusability. CTAP thereby aims at providing a common platform for complexity analysis, encouraging research collaboration and sharing of feature extraction components—to jointly advance the state-of-the-art in complexity analysis in a form that readily supports real-life use by ordinary users.
%U https://aclanthology.org/W16-4113
%P 113-119

Markdown (Informal)

[CTAP: A Web-Based Tool Supporting Automatic Complexity Analysis](https://aclanthology.org/W16-4113) (Chen & Meurers, CL4LC 2016)

• CTAP: A Web-Based Tool Supporting Automatic Complexity Analysis (Chen & Meurers, CL4LC 2016)

ACL

• Xiaobin Chen and Detmar Meurers. 2016. CTAP: A Web-Based Tool Supporting Automatic Complexity Analysis. In Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC), pages 113–119, Osaka, Japan. The COLING 2016 Organizing Committee.