liuhuanyong Goto Github PK
Name: liuhuanyong
Type: User
Company: China
Bio: 得语言者,得天下:the man who understand languages get the whole world.《老刘说NLP》技术社区作者
Location: Beijing, China
Name: liuhuanyong
Type: User
Company: China
Bio: 得语言者,得天下:the man who understand languages get the whole world.《老刘说NLP》技术社区作者
Location: Beijing, China
AbstractKnowledgeGraph, a systematic knowledge graph that concentrate on abstract thing including abstract entity and action. 抽象知识图谱,目前规模50万,支持名词性实体、状态性描述、事件性动作进行抽象。目标于抽象知识,包括抽象实体,抽象动作,抽象事件。基于该知识图谱,可以进行不同层级的实体抽象和动作抽象,这与人类真实高度概括的认知是一致的。
self complemented AlindexSpyder based on Selenium ,阿里商品指数抓取,包括淘宝采购指数,淘宝供应指数,1688供应指数。
self complemented BaiduIndexSpyder based on Selenium , index image decode and num image transfer,基于关键词的历时百度搜索指数自动采集
self complement of baike knowledge base info-box extraction by online analysis.基于互动百科,百度百科,搜狗百科的词条infobox结构化信息抽取,百科知识的融合
baike schema crawler for baidu baike , hudongbaike. 面向百度百科与互动百科的概念分类体系抓取脚本
CausalKnowledgeBase, causal knowledge base including causal pairs extracted from web text using the methods like PMI, Collocation。基于网络文本的因果知识库项目,采用PMI,搭配抽取等方法,形成因果对频繁集。
CausalDataset,因果事件对,基于非结构化新闻网页文本中进行抽取得到,目前开放100688条样本,可用于搭建因果事件图谱
Causality event extraction demo project including casual patterns and experiment on large scale corpus. 基于因果关系知识库的因果事件图谱实验项目,本项目罗列了因果显式表达的几种模式,基于这种模式和大规模语料,再经过融合等操作,可形成因果事件图谱。
self summary after attending 2018全国知识图谱与语义计算大会,China Conference on Knowledge Graph and Semantic Computing
self summary after attending CCL2018 (全国计算语言学学术会议), CCL2018参会总结,包括会议论文下载脚本,会议前言技术报告下载,以及个人的一点总结.
ChainKnowledgeGraph, 产业链知识图谱包括A股上市公司、行业和产品共3类实体,包括上市公司所属行业关系、行业上级关系、产品上游原材料关系、产品下游产品关系、公司主营产品、产品小类共6大类。 上市公司4,654家,行业511个,产品95,559条、上游材料56,824条,上级行业480条,下游产品390条,产品小类52,937条,所属行业3,946条。
chinese anti semantic word search interface based on dict crawled from online resources, ChineseAntiword,针对中文词语的反义词查询接口
WordForm,针对中文词语的笔画拆解,偏旁查询,拼音转换接口
Chinese Embedding collection incling token ,postag ,pinyin,dependency,word embedding.中文自然语言处理向量合集,包括字向量,拼音向量,词向量,词性向量,依存关系向量.共5种类型的向量
ChineseHumorSentiment, chinese humor sentiment mining including corpus build and mining nlp methods.中文文本幽默情绪计算项目,项目包括幽默文本语料库的构建,幽默计算模型,包括幽默等级识别,幽默类型识别,隐喻类型识别,隐喻情绪识别等,语言是幽默的,NLP也应该是幽默的.
An collection of Chinese nlp corpus including basic Chinese syntatic wordset, semantic wordset, historic corpus and evaluate corpus. 中文自然语言处理的语料集合,包括语义词、领域共时、历时语料库、评测语料库等。
ChineseSemanticKB,chinese semantic knowledge base, 面向中文处理的12类、百万规模的语义常用词典,包括34万抽象语义库、34万反义语义库、43万同义语义库等,可支持句子扩展、转写、事件抽象与泛化等多种应用场景。
ChineseTextualInference project including chinese corpus build and inferecence model, 中文文本推断项目,包括88万文本蕴含中文文本蕴含数据集的翻译与构建,基于深度学习的文本蕴含判定模型构建.
Cognitive Inference,认知推理、常识知识库、常识推理与常识推理评估的系统项目,以现有国内外已有的常识知识库为研究对象,从常识知识库资源建设和常识推理测试评估两个方面出发进行整理,并结合自己近几年来在逻辑性推理知识库的构建、应用以及理论思考进行介绍。具体包括已有常识知识库项目资源介绍、逻辑推理类知识库的项目实践集合、常识推理测试评估项目集合。
schemakg, a knowledge graph for schema that seeks to cover a range of things as much as possible including entity schema and event schema。试图构建起覆盖度尽可能广的schema体系,包括实体以及事件。
A concept and obvious expression pattern collection of Chinese compound event extraction which then be evolved into ComplexEventGraph,本项目提出了中文复合事件的概念与显式模式,包括条件事件、因果事件、顺承事件、反转事件等事件抽取,并形成事理图谱。
Crime assistant including crime type prediction and crime consult service based on nlp methods and crime kg,罪名法务智能项目,内容包括856项罪名知识图谱, 基于280万罪名训练库的罪名预测,基于20W法务问答对的13类问题分类与法律资讯问答功能.
DescriptionPairsExtraction, entity and it's description pairs extract program based on Albert and data back-annotation. 基于Albert与结构化数据回标思路的实体概念描述知识对抽取项目,可进一步验证基于Albert的应用可能性以及数据反标下的快速数据训练。
Syntax and Ruler-Based Doc sentiment analysis 基于依存句法规则的篇章级情感分析demo
DomainWordsDict, Chinese words dict that contains more than 68 domains, which can be used as text classification、knowledge enhance task。涵盖68个领域、共计916万词的专业词典知识库,可用于文本分类、知识增强、领域词汇库扩充等自然语言处理应用。
EventKGNELL, event knowlege graph never end learning system, a event-centric knowledge base search system,实时事理逻辑知识库终身学习系统项目和事件为核心的知识库搜索系统。包括事件概念抽取、事件因果逻辑抽取、事件数据关联推荐与推理。
Event monitor based on online news corpus including event storyline and analysis,基于给定事件关键词,采集事件资讯,对事件进行挖掘和分析。
future event predict demo based on causal event graph that covers the full industries that can predict the benefits or bad effects in accordance with the event given by the user, 基于因果事理图谱的事件预测。
An experiment and demo-level tool for text information extraction (event-triples extraction), which can be a route to the event chain and topic graph, 基于依存句法与语义角色标注的事件三元组抽取,可用于文本理解如文档主题链,事件线等应用。
FinanceEventGraph,金融领域事件图谱开放数据集,可用于事件图谱搭建于实验,包括3865个acquire并购事件、9093个invest投资事件,总计12960的事件
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