We are studying the semantic indexing method for associating other texts semantically similar and recommending them as an example to the arbitrary sites of the text read and written by a user in this project. Moreover, our subjects include paraphrasing, error correction, and template extraction for sentence generation, with the aim of developing a practical application that assists paper writing in English for non-native speakers.

Distributdc representation for similar sentence search

Inclusion criterion and crosslingually constrained word representations (by Hubert Soyer).

We propose a neural network that learns the semantic expression of phrases based on a novel standard called Inclusion criterion, which has implemented a multilanguage similar sentence search function. Furthermore, we have applied the proposed method to a Japanese–English bilingual corpus extracted from papers, and prepared a demonstration tool for English composition support CroVeWA. (Hubert Soyer, Goran Topić)