DKPro Similarity is an open source framework for text similarity. Our goal is to provide a comprehensive repository of text similarity measures which are implemented using standardized interfaces. The framework is designed to complement DKPro Core, a collection of software components for natural language processing (NLP) based on the Apache UIMA framework. DKPro Similarity comprises a wide variety of measures ranging from ones based on simple n-grams and common subsequences to high-dimensional vector comparisons and structural, stylistic, and phonetic measures. In order to promote the reproducibility of experimental results and to provide reliable, permanent experimental conditions for future studies, DKPro Similarity additionally comes with a set of full-featured experimental setups which can be run out-of-the-box and be used for future systems to built upon.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Camacho-Collados, José; Pilehvar, Mohammad Taher; Navigli, Roberto: Nasari: integrating explicit knowledge and corpus statistics for a multilingual representation of concepts and entities (2016)
- Pilehvar, Mohammad Taher; Navigli, Roberto: From senses to texts: an all-in-one graph-based approach for measuring semantic similarity (2015)