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Titlebook: Human-Inspired Computing and its Applications; 13th Mexican Interna Alexander Gelbukh,Félix Castro Espinoza,Sofía N. G Conference proceedin

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Zusammenfassung und Diskussion,hors’ profiles of various sizes using tf-idf scheme. We train SVM classifier to perform the task. We compare the method with the application of character n-grams and show that the accuracy increases when using complete syntactic n-grams.
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Finding the Most Frequent Sense of a Word by the Length of Its Definition: the MFS usually has a longer gloss, more examples of usage, and more relationships with other words (synonyms, hyponyms, etc.). In addition, we show that this effect is resource-dependent, making some algorithms to perform differently with different dictionaries.
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Complete Syntactic N-grams as Style Markers for Authorship Attributionhors’ profiles of various sizes using tf-idf scheme. We train SVM classifier to perform the task. We compare the method with the application of character n-grams and show that the accuracy increases when using complete syntactic n-grams.
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Whole-Part Relations Rule-Based Automatic Identification: Issues from Fine-Grained Error Analysisget the type of meronymy involving human entities and .. We describe with some detail the decisions that were made in order to overcome the errors produced by the system and the solutions adopted to improve its performance.
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