Sentence examples for analyzed the words from inspiring English sources

Exact(2)

So it developed software that analyzed the words in an incoming message and then selected the seemingly most salient ads among those in its inventory.

The very next day, after you've analyzed the words, approach the individual and tell him or her that he or she needs to forget about what was said.

Similar(58)

The bilingual researchers discussed and analyzed the wording of the items.

For each of these items, we analyzed the wording of the author instructions and determined whether it was "required" (i.e. a submitted manuscript would not be accepted if the item was not considered) or "recommended" (i.e. its use or fulfillment ought to be considered).

Studying for her literature degree, she had learned how to analyze the words and the themes; she had worked dutifully on her essay style, imitating academic articles.

Some measure of the prominence of foie gras in fine-dining can be seen in this word cloud analyzing the words on tasting menus at highly rated San Francisco restaurants: bigger than oysters, caviar, fennel, chanterelles.

The natural language query feature takes advantage of HANA's native text analysis ability, which can analyze the words in a question and come up with the right answer (at least that's the theory).

Swype has just launched a new Beta with two fancy new tricks: Dragon-based voice dictation, and an improved ability to analyze the words you've already typed to better determine what you're trying to type next.

Taking a fresh approach to the Celtic conundrum, Peter Forster, a geneticist at the University of Cambridge, U.K., teamed up with Alfred Toth, a linguist at the University of Zurich, Switzerland, to analyze the words as if they were genes.

By analyzing the words that contribute most significantly to the sentiment score produced by each sentiment dictionary we are able to identify words that are problematic for each sentiment dictionary at the word-level, and generate an understanding of the emotional texture of the movie review corpus.

We analyze the words in 2014 with a word shift against all 7 years of Tweets for each sentiment dictionary in each panel in the 2014 word shift Figure in Appendix S7: A. labMT scores 2014 as less happy with more negative language.

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