Using TDT2clean, we trained a PLSA model with 1000 aspects and a NNTR with the following architecture: the word and document sub-MLPs had 25 438 inputs each (corresponding to the size of the training set vocabulary), no hidden unit, and 10 outputs each; the joint word-document MLPT had 20 inputs, 25 hidden units, and one output unit.
Sample text:```Only one published paper (Enock et al. 2014) has examined this question, and thatwas in the context of anABM training study.```
Sample intent: method
Sample text:```To train our CNN for classification, we set initial learning rate to 0.01 and optimize cross-entropy loss with Adagrad [26].```
Sample intent: background



Sample text:```…posttraining and follow-up was moderate in size after self-study instruction (mean d = −0.57; Martino et al., 2011; Miller et al., 2004; Moyers et al., 2008; Sholomskas et al., 2005) and after didactic workshop training (mean d = −0.55; Baer et al., 2004; Miller et al., 2004; Moyers et al., 2008).```
Sample intent: method



Sample text:```5 concentrations were computed for each participant using a hierarchical spatiotemporal model fit with a pragmatic estimation procedure described elsewhere [30,31].```
Sample intent: background



Sample text:```…(LING)] thalamus (THA), as well as limbic/paralimbic regions [e.g. insula, superior temporal pole and inferior orbitofrontal cortex] (Table 2), which is in accordance with previous findings on functional brain networks constructed using resting-state fMRI (Achard et al., 2006; He et al., 2009b).```
Sample intent: result



Sample text:```The studies on VA are conducted for several languages and actual datasets are acquired for different languages including English [12, 13], German [14], French [15], Spanish [16] and Chinese [17–19].```
Sample intent: method
Sample text:```All MLP analyses [also known as back-propagation artificial neural networks (ANNs)] were carried out with a user-friendly neural network simulation program, NeuFrame version 3.0.0.0 (Neural Computer Sciences, Lulworth Business Centre, Totton, Southampton, UK), which runs under Microsoft Windows NT on an IBMcompatible personal computer.```
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Sample text:```We use BLEU (up to 4-grams) (Papineni et al., 2002) as evaluation metric, which computes the precision of n-grams in generated summaries with gold-standard abstracts as the reference.```
Sample intent: background



Sample text:```The studies on VA are conducted for several languages and actual datasets are acquired for different languages including English [12, 13], German [14], French [15], Spanish [16] and Chinese [17–19].```
Sample intent: method



Sample text:```Discrepancies analogous to those between our results and those of simulations have, indeed, recently been observed in the case of the binary perceptron [18], the pspin interaction spin glass [19], and in the case of fluctuating manifolds in random media [20], where dynamically frozen phases were observed in regions of parameter space in which static approaches yielded ergodic phases.```
Sample intent: result



Sample text:```5 concentrations were computed for each participant using a hierarchical spatiotemporal model fit with a pragmatic estimation procedure described elsewhere [30,31].```
Sample intent: background



Sample text:```The D-HOTM system is based on the Text Mining Infrast ucture (TMI) developed by the parallel and distributed text mining lab at Lehigh University [20].```
Sample intent: background



Sample text:```…posttraining and follow-up was moderate in size after self-study instruction (mean d = −0.57; Martino et al., 2011; Miller et al., 2004; Moyers et al., 2008; Sholomskas et al., 2005) and after didactic workshop training (mean d = −0.55; Baer et al., 2004; Miller et al., 2004; Moyers et al., 2008).```
Sample intent: method



Sample text:```…(LING)] thalamus (THA), as well as limbic/paralimbic regions [e.g. insula, superior temporal pole and inferior orbitofrontal cortex] (Table 2), which is in accordance with previous findings on functional brain networks constructed using resting-state fMRI (Achard et al., 2006; He et al., 2009b).```
Sample intent: result



Sample text:```Only one published paper (Enock et al. 2014) has examined this question, and thatwas in the context of anABM training study.```
Sample intent: method



Sample text:```The merging is based on the increase in the weighted-bycounts entropy [1] and is stopped by a threshold indicating the minimum number of training samples required to estimate a weight distribution.```
Sample intent: method