| D15-1047 | we firstly compare the coupled | bag-ofwords model | to the general model in the process |
| W13-4101 | classifier uses a standard unigram | bag-ofwords model | , simply summing the indicator |
| S13-2065 | Experiments with just a simple unigram | bag-ofwords model | show that for both the Twitter |
| W11-1721 | base supervised classifier with a | bag-ofwords model | . 4.1 Create Initial Training |
| S13-1026 | similarities obtained from distributional | bag-ofwords models | ( Sec . 2.3.2 ) ; bow-wp500 ( |
| D15-1047 | the words . Unlike the general | bag-ofwords model | which models document relationship |
| W10-2807 | word 's context . In a simple | bag-ofwords model | this might equate to one vector |
| D11-1016 | Regularization . To prevent overfitting for | bag-ofwords model | we regularize w . The L2-regularized |
| W15-4637 | MSS training set , the simple | bag-ofwords model | with a threshold t = 0.3 produced |
| D15-1161 | introduce an extension to the | bag-ofwords model | for learning words representations |
| D15-1161 | the efficiency underlying the | bag-ofwords model | , and allowing it to consider |
| W09-4102 | strictly unigrams in the traditional | bag-ofwords model | . Our approach to extracting |
| S13-2082 | conditionals etc and show that along with | bag-ofwords model | , it gives better sentiment classification |
| P06-1136 | method to improve the existing | bag-ofwords model | approach by considering the dependence |
| W10-4164 | from the word frequency in the | bag-ofwords model | ) The target word is not necessarily |
| W15-1105 | phrases using context-based , | bag-ofwords models | , i.e. , defining the structures |
| P14-1109 | beyond the standard count-based | bag-ofwords models | in NLP , and improves previous |
| D12-1047 | traditional approaches based on | bag-ofwords models | and word-based TM , because it |
| W15-1502 | architecture for the continuous | bag-ofwords model | ( Mikolov et al. , 2013 ) is |
| J12-2001 | leads to an improvement over a | bag-ofwords model | without negation , Pang , Lee |
