Titlebook: Natural Language Processing and Chinese Computing; 7th CCF Internationa Min Zhang,Vincent Ng,Hongying Zan Conference proceedings 2018 Sprin

hierarchy

書(shū)目名稱Natural Language Processing and Chinese Computing影響因子(影響力)




書(shū)目名稱Natural Language Processing and Chinese Computing影響因子(影響力)學(xué)科排名




書(shū)目名稱Natural Language Processing and Chinese Computing網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Natural Language Processing and Chinese Computing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Natural Language Processing and Chinese Computing被引頻次




書(shū)目名稱Natural Language Processing and Chinese Computing被引頻次學(xué)科排名




書(shū)目名稱Natural Language Processing and Chinese Computing年度引用




書(shū)目名稱Natural Language Processing and Chinese Computing年度引用學(xué)科排名




書(shū)目名稱Natural Language Processing and Chinese Computing讀者反饋




書(shū)目名稱Natural Language Processing and Chinese Computing讀者反饋學(xué)科排名

漂浮

https://doi.org/10.1007/978-3-319-99501-4artificial intelligence; classification; data mining; HCI; human-computer interaction; information retrie

nephritis

Pelvic-Floor

移動(dòng)

indenture

Admonish

PANIC

abstemious

Which Embedding Level is Better for Semantic Representation? An?Empirical Research on Chinese Phrased investigate the performance of the two basic units. Empirical results show that with all composing methods, word embedding out performs character embedding on both tasks, which indicates that word level is more suitable for composing semantic representation.

破布

Improving Word Embeddings for Antonym Detection Using Thesauri and SentiWordNetord in SentiWordNet. We conduct evaluations on three relevant tasks, namely GRE antonym detection, word similarity, and semantic textual similarity. The experiment results show that our antonym-sensitive embedding outperforms common word embeddings in these tasks, demonstrating the efficacy of our methods.