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检索条件"任意字段=6th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2017"

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6th ccf international conference on natural language processing and chinese computing, nlpcc 2017

6th CCF International Conference on Natural Language Process...

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6th ccf international conference on natural language processing and chinese computing, nlpcc 2017

ISBN: (纸本)9783319736174

the proceedings contain 86 papers. the special focus in this conference is on natural language processing and chinese computing. the topics include: A deep learning way for disease name representation and normalization;Externally controllable RNN for implicit discourse relation classification;random projections with bayesian priors;a convolutional attention model for text classification;shortcut sequence tagging;look-ahead attention for generation in neural machine translation;modeling indicative context for statistical machine translation;augmenting neural sentence summarization through extractive summarization;a semantic concept based unknown words processing method in neural machine translation;Research on mongolian speech recognition based on FSMN;using bilingual segments to improve interactive machine translation;Unsupervised automatic text style transfer using LSTM;optimizing topic distributions of descriptions for image description translation;automatic document metadata extraction based on deep networks;a semantic representation enhancement method for chinese news headline classification;neural domain adaptation with contextualized character embedding for chinese word segmentation;identification of influential users based on topic-behavior influence tree in social networks;abstractive document summarization via neural model with joint attention;an effective approach for chinese news headline classification based on multi-representation mixed model with attention and ensemble learning;Cascaded LSTMs based deep reinforcement learning for goal-driven dialogue;domain-specific chinese word segmentation with document-level optimization;will repeated reading benefit natural language understanding?;a deep convolutional neural model for character-based chinese word segmentation;chinese zero pronoun resolution: A chain to chain approach;towards better chinese zero pronoun resolution from discourse perspective;extractive single document summarization via multi-feature

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Overview of the nlpcc 2017 Shared Task: Single Document Summarization 6th

Overview of the NLPCC 2017 Shared Task: Single Document Summ...

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6th ccf international conference on natural language processing and chinese computing (nlpcc)

作者： Hua, Lifeng Wan, Xiaojun Li, Lei Toutiao AI Lab Beijing Peoples R China Peking Univ Inst Comp Sci & Technol Beijing Peoples R China

ISBN: (纸本)9783319736181;9783319736174

In this paper, we give an overview for the shared task at the 6th ccf conference on natural language processing & chinese computing (nlpcc 2017): single document summarization. Document summarization aims at conveying important information and generating significantly short summaries for original long documents. this task focused on summarizing the news articles and released a large corpus, TTNews corpus (TTNews corpus can be downloaded at https://***/s/1bppQ4z1), which was collected for single document summarization in chinese. In this paper, we will introduce the task, the corpus, the participating teams and the evaluation results.

关键词： Single document summarization nlpcc 2017 TTNews corpus

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Overview of the nlpcc 2017 Shared Task: chinese News Headline Categorization 6th

Overview of the NLPCC 2017 Shared Task: Chinese News Headlin...

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6th ccf international conference on natural language processing and chinese computing (nlpcc)

作者： Qiu, Xipeng Gong, Jingjing Huang, Xuanjing Fudan Univ Sch Comp Sci 825 Zhangheng Rd Shanghai Peoples R China

ISBN: (纸本)9783319736181;9783319736174

In this paper, we give an overview for the shared task at the ccf conference on natural language processing & chinese computing (nlpcc 2017): chinese News Headline Categorization. the dataset of this shared task consists 18 classes, 12,000 short texts along with corresponded labels for each class. the dataset and example code can be accessed at https://***/FudanNLP/n1pcc2017_news_ headline_categorization.

关键词： natural language processing systems

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Overview of the nlpcc 2017 Shared Task: Open Domain chinese Question Answering 6th

Overview of the NLPCC 2017 Shared Task: Open Domain Chinese ...

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6th ccf international conference on natural language processing and chinese computing (nlpcc)

作者： Duan, Nan Tang, Duyu Microsoft Res Asia Beijing Peoples R China

ISBN: (纸本)9783319736181;9783319736174

In this paper, we give the overview of the open domain Question Answering (or open domain QA) shared task in the nlpcc 2017. We first review the background of QA, and then describe two open domain chinese QA tasks in this year's nlpcc, including the construction of the benchmark datasets and the evaluation metrics. the evaluation results of submissions from participating teams are presented in the experimental part.

关键词： Question answering Knowledge-based QA Document-based QA Table-based QA

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Overview of the nlpcc-ICCPOL 2017 Shared Task: Social Media User Modeling 6th

Overview of the NLPCC-ICCPOL 2017 Shared Task: Social Media ...

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6th ccf international conference on natural language processing and chinese computing (nlpcc)

作者： Zhang, Fuzheng Lian, Defu Xie, Xing Microsoft Res Asia Beijing Peoples R China

ISBN: (纸本)9783319736181;9783319736174

In this paper, we give the overview of the social media user modeling shared task in the nlpcc-ICCPOL 2017. We first review the background of social media user modeling, and then describe two social media user modeling tasks in this year's nlpcc-ICCPOL, including the construction of the benchmark datasets and the evaluation metrics. the evaluation results of submissions from participating teams are presented in the experimental part.

关键词： User modeling Social media Recommendation

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Overview of the nlpcc 2017 Shared Task: chinese Word Semantic Relation Classification 6th

Overview of the NLPCC 2017 Shared Task: Chinese Word Semanti...

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6th ccf international conference on natural language processing and chinese computing (nlpcc)

作者： Wu, Yunfang Zhang, Minghua Peking Univ Minist Educ Key Lab Computat Linguist Beijing 100871 Peoples R China

ISBN: (纸本)9783319736181;9783319736174

Word semantic relation classification is a challenging task for natural language processing, so we organize a semantic campaign on this task at nlpcc 2017. the dataset covers four kinds of semantic relations (synonym, antonym, hyponym and meronym), and there are 500 word pairs per category. Together 17 teams submit their results. In this paper, we describe the data construction and experimental setting, make an analysis on the evaluation results, and make a brief introduction to some of the participating systems.

关键词： Word semantic relation Synonym Antonym Hyponym Meronym

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A Retrieval-Based Matching Approach to Open Domain Knowledge-Based Question Answering 6th

A Retrieval-Based Matching Approach to Open Domain Knowledge...

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6th ccf international conference on natural language processing and chinese computing (nlpcc)

作者： Zhang, Han Zhu, Muhua Wang, Huizhen Northeast Univ Nat Language Proc Lab Shenyang Liaoning Peoples R China Tencent AI Lab Shenzhen Peoples R China

ISBN: (纸本)9783319736181;9783319736174

In this paper, we propose a retrieval and knowledge-based question answering system for the competition task in nlpcc 2017. Regarding the question side, our system uses a ranking model to score candidate entities to detect a topic entity from questions. then similarities between the question and candidate relation chains are computed, based on which candidate answer entities are ranked. By returning the highest scored answer entity, our system finally achieves the Fl-score of 41.96% on test set of nlpcc 2017. Our current system focuses on solving single-relation questions, but it can be extended to answering multiple-relation questions.

关键词： Question answering Knowledge base Entity linking Relation chain inference

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Linking Entities in chinese Queries to Knowledge Graph 4th

Linking Entities in Chinese Queries to Knowledge Graph

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4th ccf international conference on natural language processing and chinese computing (nlpcc)

作者： Li, Jun Pan, Jinxian Ye, Chen Huang, Yong Wen, Danlu Wang, Zhichun Beijing Normal Univ Beijing Peoples R China Capital Normal Univ Beijing Peoples R China

ISBN: (纸本)9783319252070;9783319252063

this paper presents our approach for nlpcc 2015 shared task, Entity Recognition and Linking in chinese Search Queries. the proposed approach takes a query as input, and generates a ranked mention-entity links as results. It combines several different metrics to evaluate the probability of each entity link, including entity relatedness in the given knowledge graph, document similarity between query and the virtual document of entity in the knowledge graph. In the evaluation, our approach gets 33.2% precision and 65.2% recall, and ranks the 6th among all the 14 teams according to the average F1-measure.

关键词： Entity linking chinese query Knowledge graph

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Classification of chinese Word Semantic Relations 6th

Classification of Chinese Word Semantic Relations

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6th ccf international conference on natural language processing and chinese computing (nlpcc)

作者： Li, Changliang Ma, Teng Chinese Acad Sci Inst Automat Beijing Peoples R China Wuhan Univ Sch Math & Stat Wuhan 430072 Hubei Peoples R China

ISBN: (纸本)9783319736181;9783319736174

Classification of word semantic relation is a challenging task in natural language processing (NLP) field. In many practical applications, we need to distinguish words with different semantic relations. Much work relies on semantic resources such as Tongyici Cilin and HowNet, which are limited by the quality and size. Recently, methods based on word embedding have received increasing attention for their flexibility and effectiveness in many NLP tasks. Furthermore, word vector offset implies words semantic relation to some extent. this paper proposes a novel framework for identifying the chinese word semantic relation. We combine semantic dictionary, word vector and linguistic knowledge into a classification system. We conduct experiments on the chinese Word Semantic Relation Classification shared task of nlpcc 2017. We rank No.1 with the result of F1 value 0.859. the results demonstrate that our method is very scientific and effective.

关键词： Word relation classification Word vector Semantic lexicons Linguistic knowledge

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A chinese Question Answering System for Single-Relation Factoid Questions 6th

A Chinese Question Answering System for Single-Relation Fact...

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6th ccf international conference on natural language processing and chinese computing (nlpcc)

作者： Lai, Yuxuan Jia, Yanyan Lin, Yang Feng, Yansong Zhao, Dongyan Peking Univ Inst Comp Sci & Technol Beijing Peoples R China

ISBN: (纸本)9783319736181;9783319736174

Aiming at the task of open domain question answering based on knowledge base in nlpcc 2017, we build a question answering system which can automatically find the promised entities and predicates for single-relation questions. After a features based entity linking component and a word vector based candidate predicates generation component, deep convolutional neural networks are used to rerank the entitypredicate pairs, and all intermediary scores are used to choose the final predicted answers. Our approach achieved the F1-score of 47.23% on test data which obtained the first place in the contest of nlpcc 2017 Shared Task 5 (KBQA sub-task). Furthermore, there are also a series of experiments which can help other developers understand the contribution of every part of our system.

关键词： natural language question answering Knowledge base Information extraction Deep convolutional neural network

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