Titlebook: Natural Language Processing and Chinese Computing; 6th CCF Internationa Xuanjing Huang,Jing Jiang,Yu Hong Conference proceedings 2018 Sprin

用手捏

Jointly Modeling Intent Identification and Slot Filling with Contextual and Hierarchical Informationork has made use of either hierarchical or contextual information when jointly modeling intent classification and slot filling, proving that either of them is helpful for joint models. This paper proposes a cluster of joint models to encode both types of information at the same time. Experimental re

压迫

Augmenting Neural Sentence Summarization Through Extractive Summarizationvious works can only utilize lead sentences as the input to generate the abstractive summarization, which ignores crucial information of the document. To alleviate this problem, we propose a novel approach to improve neural sentence summarization by using extractive summarization, which aims at taki

meditation

Cascaded LSTMs Based Deep Reinforcement Learning for Goal-Driven Dialoguestems. There are three parts in this model. A Long Short-Term Memory (LSTM) at the bottom of the network encodes utterances in each dialogue turn into a turn embedding. Dialogue embeddings are learned by a LSTM at the middle of the network, and updated by the feeding of all turn embeddings. The top

陶器

Tonometry

An Ensemble Approach to Conversation Generation paper gives a detailed description about an ensemble system for short text conversation generation. The proposed system consists of four subsystems, a quick response candidates selecting module, an information retrieval system, a generation-based system and an ensemble module. An advantage of this

FORGO

表状态

Large-Scale Simple Question Generation by Template-Based Seq2seq Learninge’s no large-scale question-answer corpora available for Chinese question answering over knowledge bases. In this paper, we present a 28M Chinese Q&A corpora based on the Chinese knowledge base provided by NLPCC2017 KBQA challenge. We propose a novel neural network architecture which combines templa

PAC

enumaerate

Geography Gaokao-Oriented Knowledge Acquisition for Comparative Sentences Based on Logic Programming high knowledge skill. As a preliminary attempt to address this problem, we build a geography Gaokao-oriented knowledge acquisition system for comparative sentences based on logic programming to help solve real geography examinations. Our work consists of two consecutive tasks: identify comparative

Conscientious

Chinese Question Classification Based on Semantic Joint Featuresxts and those short texts like comments on product. They generally contain interrogative words such as who, which, where or how to specify the information required, and include complete grammatical components in the sentence. Based on these characteristics, we propose a more effective feature extrac