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doc2vec, generates distributed representations of variable-length pieces of texts, such as sentences, paragraphs, or entire documents. [14] [15] doc2vec has been implemented in the C, Python and Java/Scala tools (see below), with the Java and Python versions also supporting inference of document embeddings on new, unseen documents.
The standard 'vanilla' approach to locate the end of a sentence: [clarification needed] (a) If it is a period, it ends a sentence. (b) If the preceding token is in the hand-compiled list of abbreviations, then it does not end a sentence. (c) If the next token is capitalized, then it ends a sentence. This strategy gets about 95% of sentences ...
Text segmentation is the process of dividing written text into meaningful units, such as words, sentences, or topics.The term applies both to mental processes used by humans when reading text, and to artificial processes implemented in computers, which are the subject of natural language processing.
The bag-of-words model (BoW) is a model of text which uses a representation of text that is based on an unordered collection (a "bag") of words.It is used in natural language processing and information retrieval (IR).
A stylistic depiction of values inside of a so-named comma-separated values (CSV) text file. The commas (shown in red) are used as field delimiters. A delimiter is a sequence of one or more characters for specifying the boundary between separate, independent regions in plain text, mathematical expressions or other data streams.
Real cheese that’s been overheated can separate into oily puddles. The emulsifiers found in American cheese may not be easy to pronounce, but they do eliminate that issue so you get perfectly ...
Sentence extraction is a technique used for automatic summarization of a text. In this shallow approach, statistical heuristics are used to identify the most salient sentences of a text. Sentence extraction is a low-cost approach compared to more knowledge-intensive deeper approaches which require additional knowledge bases such as ontologies ...
The real hack here is using your calendar as your to-do list. If it doesn’t fit into your calendar, it’s not getting done. An hour in the morning for research. Ninety minutes after lunch to write.