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TextualModelGenerator can be used to extract terminology from a textual collection. This is an evolution of the GATE Toolkit’s GATE TextualModelGenerator, a java application which could extract the best term from a collection of texts. The GATE TextualModelGenerator was, however, a standalone application. It required compilation of several grammars from the GATE toolkit, and then processing of the source texts with these grammars. TextualModelGenerator requires no compilation and no processing other than simple string operations. Hence the tool is faster and simpler to use.
TextualModelGenerator has been tested against the GATE test collections. It successfully extracted the best term for over 10,000 texts in the case of the Chicago Manual of Style. The tool is also more robust: it is able to handle multiple terminologies.
The term extraction may be pre-computed, or it may be generated in real time as the texts are being processed. The tool is able to read the source texts from any input format, although it expects all input files to be of a certain format. The tool uses the terms’ structure to read the texts.
TextualModelGenerator also offers several processing methods: term frequency-inverse document frequency (tf-idf), KLD (Chi^2), or mutual information. It is able to process a collection of text in multiple threads. Hence multiple threads can be used to increase the speed of the application.
Different grammars can be provided for term extraction. They can be provided as a collection of files that can be specified in the configuration file. TextualModelGenerator can also be configured with external resources, such as additional dictionaries or thesauri.
TextualModelGenerator is a multi-threaded application. This means that it has multiple threads reading from the files provided. Each thread has its own configuration file and handles its own threading data. This allows users to configure the application in different ways by using different threads. Each thread can be configured with its own grammar or dictionaries. This makes it possible to define the term extraction using different grammars or dictionaries. This also means that each thread is a separate program and can be started separately.
TextualModelGenerator Summary:
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The application is a framework for extracting terms from text. The application does not extract terms by itself. It provides a framework for extracting the best term for a collection of texts. For 70238732e0
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May 31, 2022