Investigating the Role of Prior Disambiguation in Deep-learning Compositional Models of Meaning
نویسندگان
چکیده
This paper aims to explore the effect of prior disambiguation on neural networkbased compositional models, with the hope that better semantic representations for text compounds can be produced. We disambiguate the input word vectors before they are fed into a compositional deep net. A series of evaluations shows the positive effect of prior disambiguation for such deep models.
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ورودعنوان ژورنال:
- CoRR
دوره abs/1411.4116 شماره
صفحات -
تاریخ انتشار 2014