Abstract: A document analysis device that includes a memory operable to store a machine learning model configured to receive a sentence as an input and to output a classification identifier that is associated with a sentence type for the received sentence. The device further includes an artificial intelligence (AI) processing engine configured to receive a document comprising text, to sentences within the document, and to classify the sentences using the machine learning model. The AI processing engine is further configured to identify tagging rules for the document and to annotate one or more sentences from the document with a sentence type that matches a sentence type that is identified by the tagging rules for the document.

Abstract: A document analysis device that includes an artificial intelligence (AI) processing engine configured to receive a set of input sentences, to select a first sentence from the set of input sentences, and to compare the first sentence to previously classified sentences. The AI processing engine is further configured to compute similarity scores between the first sentence and the previously classified sentences, to identify a second sentence from the previously classified sentences with a similarity score greater than or equal to a similarity score threshold value, to identify a sentence type that is associated with the second sentence, and to associate the first sentence with the sentence type. The AI processing engine is further configured to add the first sentence to the set of training data for the machine learning model and to train the machine learning model using the set of training data.

Abstract: A document analysis device that includes an artificial intelligence (AI) processing engine configured to identify common words between a first sentence and a second sentence and store the common words in first data structure. The AI processing engine is further configured to identify unique words from among the first sentence and the second sentence and store each unique word in a second data structure. The AI processing engine is further configured to compute a first similarity score and to compare the first similarity score to a similarity score threshold value. The AI processing engine is further configured to indicate the first sentence and the second sentence are similar when the first similarity score is greater than or equal to the similarity score threshold value and to indicate the first sentence and the second sentence are not similar when the first similarity score is less than the similarity score threshold value.

Abstract: A document analysis device that includes an artificial intelligence (AI) processing engine configured to receive training data, to select a sentence from the training data, and to compute a first set of similarity scores between the selected sentence and other sentences from the training data. The AI processing engine is further configured to determine a set count that is equal to a number of similarity scores in the first set of similarity scores that exceed a similarity score threshold value and to compare the set count to a set outlier threshold value. The AI processing engine is further configured to keep the selected sentence in the training data when the set count is greater than or equal to the set outlier threshold value and to remove the selected sentence from the training data when the set count is less than the set outlier threshold value.

Abstract: A document analysis device that includes an artificial intelligence (AI) processing engine configured to receive training data, to select a sentence from the training data, and to compute a first set of similarity scores between the selected sentence and other sentences from the training data. The AI processing engine is further configured to determine a set count that is equal to a number of similarity scores in the first set of similarity scores that exceed a similarity score threshold value and to compare the set count to a set outlier threshold value. The AI processing engine is further configured to keep the selected sentence in the training data when the set count is greater than or equal to the set outlier threshold value and to remove the selected sentence from the training data when the set count is less than the set outlier threshold value.

Abstract: A document analysis device that includes a memory operable to store a machine learning model configured to receive a sentence as an input and to output a classification identifier that is associated with a sentence type for the received sentence. The device further includes an artificial intelligence (AI) processing engine configured to receive a document comprising text, to sentences within the document, and to classify the sentences using the machine learning model. The AI processing engine is further configured to identify tagging rules for the document and to annotate one or more sentences from the document with a sentence type that matches a sentence type that is identified by the tagging rules for the document.

Abstract: A document analysis device that includes an artificial intelligence (AI) processing engine configured to receive a set of input sentences, to select a first sentence from the set of input sentences, and to compare the first sentence to previously classified sentences. The AI processing engine is further configured to compute similarity scores between the first sentence and the previously classified sentences, to identify a second sentence from the previously classified sentences with a similarity score greater than or equal to a similarity score threshold value, to identify a sentence type that is associated with the second sentence, and to associate the first sentence with the sentence type. The AI processing engine is further configured to add the first sentence to the set of training data for the machine learning model and to train the machine learning model using the set of training data.

Abstract: A document analysis device that includes an artificial intelligence (AI) processing engine configured to identify common words between a first sentence and a second sentence and store the common words in first data structure. The AI processing engine is further configured to identify unique words from among the first sentence and the second sentence and store each unique word in a second data structure. The AI processing engine is further configured to compute a first similarity score and to compare the first similarity score to a similarity score threshold value. The AI processing engine is further configured to indicate the first sentence and the second sentence are similar when the first similarity score is greater than or equal to the similarity score threshold value and to indicate the first sentence and the second sentence are not similar when the first similarity score is less than the similarity score threshold value.