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TAPoR (Text Analysis Portal for Research) is a gateway that highlights tools and code snippets usable for textual criticism of all types. The project is housed at the University of Alberta , and is currently led by Geoffrey Rockwell, Stéfan Sinclair, Kirsten C. Uszkalo, and Milena Radzikowska.
GATE – general Architecture for Text Engineering, an open-source toolbox for natural language processing and language engineering. Gensim – large-scale topic modelling and extraction of semantic information from unstructured text . KH Coder – for Quantitative Content Analysis or Text Mining; The KNIME Text Processing extension.
PDF is used for representing two-dimensional documents in a manner independent of the application software, hardware, and operating system. Each PDF file encapsulates a complete description of a fixed-layout 2D document that includes the text, fonts, images, and 2D vector graphics which compose the documents.
Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." [1] Written resources may include websites, books, emails, reviews, and ...
In addition to root-level robots.txt files, robots exclusion directives can be applied at a more granular level through the use of Robots meta tags and X-Robots-Tag HTTP headers. The robots meta tag cannot be used for non-HTML files such as images, text files, or PDF documents.
To avoid generating code that includes unistd.h, %option nounistd should be used. Another issue is the call to isatty (a Unix library function), which can be found in the generated code. The %option never-interactive forces flex to generate code that does not use isatty. [14]
Computer-assisted (or aided) qualitative data analysis software (CAQDAS) offers tools that assist with qualitative research such as transcription analysis, coding and text interpretation, recursive abstraction, content analysis, discourse analysis, [1] grounded theory methodology, etc.
It uses machine learning techniques to create a semantic interpreter, which extracts text fragments from articles into a sorted list. The fragments are sorted by how related they are to the surrounding text. Latent semantic analysis (LSA) is another common method that does not use ontologies, only considering the text in the input space.