Titlebook: Natural Language Processing and Chinese Computing; 8th CCF Internationa Jie Tang,Min-Yen Kan,Hongying‘Zan Conference proceedings 2019 Sprin

fertilizer

FlexNER: A Flexible LSTM-CNN Stack Framework for Named Entity RecognitionSpanish, Dutch and Chinese, and biomedical fields, such as identifying the chemicals and gene/protein terms from scientific works. Experimental results demonstrate the good performance of this framework.

滴注

Vo2-Max

IPRE: A Dataset for Inter-Personal Relationship Extraction IPRE has over 41,000 labeled sentences for 34 types of relations, including about 9,000 sentences annotated by workers. Our data is the first dataset for inter-personal relationship extraction. Additionally, we define three evaluation tasks based on IPRE and provide the baseline systems for further comparison in future work.

暗指

Shared-Private LSTM for Multi-domain Text Classificationl network. The advantage of SP-LSTM is that it allows domain-private information to communicate with each other during the encoding process, and it is faster than LSTM due to the parallel mechanism. Results on text classification across 16 domains indicate that SP-LSTM outperforms state-of-the-art shared-private architecture.

Diastole

正式演说

0302-9743 Learning for NLP; Machine Translation; NLP Applications; NLP for Social Network; NLP Fundamentals; Text Mining; Short Papers; Explainable AI Workshop; Student Workshop: Evaluation Workshop.    .978-3-030-32235-9978-3-030-32236-6Series ISSN 0302-9743 Series E-ISSN 1611-3349

pulmonary-edema

虚情假意

languor

Classification over Clustering: Augmenting Text Representation with Clusters Helps!cs and composing them together to get a set of cluster vectors, which are then concatenated as the final text representation. Evaluation on five classification benchmarks proves the effectiveness of our method. We further conduct visualization analysis showing statistical clustering results and verifying the validity of our motivation.

CURB

Conference proceedings 2019elected from 492 submissions. They are organized in the following topical sections: Conversational Bot/QA/IR.; .Knowledge graph/IE; Machine Learning for NLP; Machine Translation; NLP Applications; NLP for Social Network; NLP Fundamentals; Text Mining; Short Papers; Explainable AI Workshop; Student Workshop: Evaluation Workshop.    .