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Contrasting with the traditional "key words" approach to mathematic word problems, the alternative way presented in Chapter 4 from the perspective of FLA helps students recognize the connection between the language patterns used in a word problem and the mathematic knowledge to be applied in tackling it (p. 66).
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Moreover, although there were some variations in the patterns between the 10 knappers, the toolmaking and language patterns within each individual were very closely aligned suggesting, the team concludes, that the same brain areas recruited in both tasks.
Once the intra-sentential language patterns are discovered, the frequently co-occurred patterns between the cause and effect text spans are then combined to form a set of inter-sentential language patterns.
The training set was used to generate the inter-sentential language patterns and word pairs.
The inter-sentential language patterns can capture associations among multiple words within and between sentences, thus can provide more precise information than word pairs.
Therefore, once the intra-sentential language patterns for cause and effect events are generated using each of the abovementioned methods, the next step is to generate inter-sentential language patterns by finding frequently co-occurring patterns between the cause and effect text spans.
This section describes the use of inter-sentential language patterns to detect causality between sentences, focusing on the detection of implicit cause-effect relations.
Finally, the acquired inter-sentential language patterns are used as features to detect causality between sentences.
The resulting inter-sentential language patterns are those with a minimum confidence score.
As each sentence pair is transformed into pattern representation, it is represented by a single or multiple inter-sentential language patterns depending on the number of patterns the sentence pair matched in the set of discovered inter-sentential language patterns.
Therefore, this study proposes the use of inter-sentential language patterns such as ≪broke up, boyfriend>,
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CEO of Professional Science Editing for Scientists @ prosciediting.com