Qingxia Liu qxliu.nju@gmail.com A Generative Interpretation of RDF Dataset  and its Application in Summarization Qingxia Liu qxliu.nju@gmail.com 2019/4/6.

Slides:



Advertisements
Similar presentations
Data Mining and the Web Susan Dumais Microsoft Research KDD97 Panel - Aug 17, 1997.
Advertisements

Processing XML Keyword Search by Constructing Effective Structured Queries Jianxin Li, Chengfei Liu, Rui Zhou and Bo Ning Swinburne University of Technology,
1 gStore: Answering SPARQL Queries Via Subgraph Matching Presented by Guan Wang Kent State University October 24, 2011.
 Copyright 2008 Digital Enterprise Research Institute. All rights reserved. Digital Enterprise Research Institute Context Dependent Reasoning.
IVITA Workshop Summary Session 1: interactive text analytics (Session chair: Professor Huamin Qu) a) HARVEST: An Intelligent Visual Analytic Tool for the.
Game Theory 窦衍旭. 什么是博弈论 博弈论,经济学中很著名的理论, 就是在 信息不对称的情况下根据对手可能作出的 决策作出决策,通俗地说,如果我这样做, 那么对手会怎样做,而对手基于我的做法 作出决策,我又该怎么做来应对。
Ontology Summarization Based on RDF Sentence Graph Written by: Xiang Zhang, Gong Cheng, Yuzhong Qu Presented by: Sophya Kheim.
Research Problems in Semantic Web Search Varish Mulwad ____________________________ 1.
第二章 随机变量及其分布 第一节 随机变量及其分布函数 一、随机变量 用数量来表示试验的基本事件 定义 1 设试验 的基本空间为 , ,如果对试验 的每一个基 本事件 ,规定一个实数记作 与之对应,这样就得到一个定义在基本空 间 上的一个单值实函数 ,称变量 为随机变量. 随机变量常用字母 、 、 等表示.或用.
Query Biased Snippet Generation in XML Search Yi Chen Yu Huang, Ziyang Liu, Yi Chen Arizona State University.
Graph Algebra with Pattern Matching and Aggregation Support 1.
Temporal Event Map Construction For Event Search Qing Li Department of Computer Science City University of Hong Kong.
Supporting the Automatic Construction of Entity Aware Search Engines Lorenzo Blanco, Valter Crescenzi, Paolo Merialdo, Paolo Papotti Dipartimento di Informatica.
Some studies on Vietnamese multi-document summarization and semantic relation extraction Laboratory of Data Mining & Knowledge Science 9/4/20151 Laboratory.
Page 1 WEB MINING by NINI P SURESH PROJECT CO-ORDINATOR Kavitha Murugeshan.
An Integrated Approach to Extracting Ontological Structures from Folksonomies Huairen Lin, Joseph Davis, Ying Zhou ESWC 2009 Hyewon Lim October 9 th, 2009.
Semantic data model
Hive – A Warehousing Solution Over a MapReduce Framework Bingbing Liu
Q2Semantic: A Lightweight Keyword Interface to Semantic Search Haofen Wang 1, Kang Zhang 1, Qiaoling Liu 1, Thanh Tran 2, and Yong Yu 1 1 Apex Lab, Shanghai.
Hierarchical Focus+Context Heterogeneous Network Visualization
人教修订版 高中一年级 ( 下 ) Unit 18. Main Topics Part 1 (Para.1) Part 2 (Para.2-3) Part 3 (Para.4) Part 4 (Para.5) Population,ethnic groups and the languages.
Mining real world data Web data. World Wide Web Hypertext documents –Text –Links Web –billions of documents –authored by millions of diverse people –edited.
Semi-Automatic Quality Assessment of Linked Data without Requiring Ontology Saemi Jang, Megawati, Jiyeon Choi, and Mun Yong Yi KIRD, KAIST NLP&DBPEDIA.
VLDB2005 CMS-ToPSS: Efficient Dissemination of RSS Documents Milenko Petrovic Haifeng Liu Hans-Arno Jacobsen University of Toronto.
Using linked data to interpret tables Varish Mulwad September 14,
Shridhar Bhalerao CMSC 601 Finding Implicit Relations in the Semantic Web.
2015/12/121 Extracting Key Terms From Noisy and Multi-theme Documents Maria Grineva, Maxim Grinev and Dmitry Lizorkin Proceeding of the 18th International.
表内除法(一) 用 2 ~ 6 的乘法口诀 求商( 2 ). 填一填,并说出用哪句乘法口诀。 12÷6 = 6÷2 = 12÷4 = 8÷4 = 9÷3 = 10÷2 = ×7 = 6×6 = 7×2 = 4×8 = 5×6 = 7×4 =
GoRelations: an Intuitive Query System for DBPedia Lushan Han and Tim Finin 15 November 2011
Meta-Path-Based Ranking with Pseudo Relevance Feedback on Heterogeneous Graph for Citation Recommendation By: Xiaozhong Liu, Yingying Yu, Chun Guo, Yizhou.
SCI 数据库检索练习参考 本练习完全依照 SCI 数据库实际检索过程而 实现。 本练习完全依照 SCI 数据库实际检索过程而 实现。 练习中,选择了可以举一反三的题目,读 者可以根据题目进行另外的检索练习,如: 可将 “ 与 ” 运算检索改为 “ 或 ” 、 “ 非 ” 运算检索 等等。 练习中,选择了可以举一反三的题目,读.
Optimal SenTree: representing RDF sentence as a tree with minimal reversed triples Qingxia Liu
Quick review Data Structures.
Unit 2 Topic 1 I have a small nose. Section D.
Clustering of Web pages
Unit 1.
Business Statistics Topic 5
Websoft Research Group
Probabilistic Data Management
The Graph Structure of RDF Sentences
Ontology Evaluation ارزیابی آنتولوژی
Query Construct Interfaces of RDF Data an introduction
Ontology Partition for Browsing
A Schema and Instance Based RDF Dataset Summarization Tool
NJVR: The NanJing Vocabulary Repository
Gong Cheng, Yanan Zhang, and Yuzhong Qu
Zachary Cleaver Semantic Web.
Weiyi Ge, Gong Cheng, Huiying Li, Yuzhong Qu
Text Categorization Document classification categorizes documents into one or more classes which is useful in Information Retrieval (IR). IR is the task.
Property consolidation for entity browsing
Type-directed Topic Segmentation of Entity Descriptions
جستجو در وب عميق ارائه‌دهنده: حسين شريفي‌پناه
RDF graph summaries 金成 2014/11/3.
Finding Patterns in a Knowledge Base using Keywords to Compose Table Answers/VLDB2015 报告人:胡信晖 2019/1/18.
Qingxia Liu Interactive Hierarchical Tag Clouds for Summarizing Spatiotemporal Social Contents [ICDE 2014] Kang, Wei, Anthony KH Tung,
Magnet & /facet Zheng Liang
Qingxia Liu Optimal SenTree: representing RDF sentence as a tree with minimal reversed triples Qingxia Liu
Towards Exploratory Relationship Search: A Clustering-Based Approach
Danyun Xu, Gong Cheng*, Yuzhong Qu
相关工作报告 施林锋 丁文韬 于佳婕.
Entity Description Pattern Extraction and Their Usage in Entity Query
Different Sources Give us Different Result
Generating Hierarchical link patterns based on concept lattice for Navigating the Web of Data Liang Zheng.
An Ontology-Based Method for Extracting Semantic Relations from Descriptive Text Da Huang.
Integrating Class Hierarchies
Promising “Newer” Technologies to Cope with the
Embedding based entity summarization
Heterogeneous Graph Convolutional Network
Introduction Dataset search
CVPR 2019 Poster.
Presentation transcript:

Qingxia Liu qxliu.nju@gmail.com A Generative Interpretation of RDF Dataset  and its Application in Summarization Qingxia Liu qxliu.nju@gmail.com 2019/4/6 Websoft Research Group

Motivation & Goal To understand a dataset Goal Applications Build an abstract model which fits the actual data most Applications RDF dataset summarization Query generation

Traditional Perspectives Triple set A set of triples (?s, ?p, ?o) Entity graph Node link graph of entity nodes Vertex clustering: type, attribute[1][2][4] Pattern extraction[5] Sentence graph a graph of RDF sentences Salient sentence extraction: centrality measurements[3] Topic graph? nodes are equivalent if they have the same set of outgoing and incoming paths.

What is Topic? A topic is … A distribution of a bag of words A facet of data that describes an entity 人的基本信息、文章发表信息、学习信息

What is Topic? A Generative Story Topic分布的分布:Dirichlet分布; 一个topic是一个一般骰子;每个topic对应一个词分布; 每个entity,选择一个topic分布(即骰子的分布),从这个topic分布(一堆骰子)中,选K个骰子(word分布),每个骰子投一次各得到一个word;

Why topic? Why not Classes? Conceptual meaning of the entity, not the feature of data Usage of concepts from different ontologies Existence of wrong, superfluous or insufficient labeled concepts Danyun Xu Classes: graduateStudent, Person Properties(actual data): as a person: name, gender, emailAddress, homepage, telephone as a student: takenCourse, memberOf as a reseacher: undergraduateDegreeFrom, advisor, publication

Why topic? What’s the dataset talking about? Basic info of people in a city? name,gender, occupation, weight, height,… Course taken data in a university? takenCourse, grade Info about researchers? Degree, undergraduateDegreeFrom, publication

Preliminary Results topics on LUBM

To Do More investigation Experimental effects Evaluate methods

References Campinas, Stéphane, Renaud Delbru, and Giovanni Tummarello. "Efficiency and precision trade-offs in graph summary algorithms." Proceedings of the 17th International Database Engineering & Applications Symposium. ACM, 2013. Tran, Thanh, Lei Zhang, and Rudi Studer. "Summary models for routing keywords to Linked Data sources." The Semantic Web–ISWC 2010. Springer Berlin Heidelberg, 2010. 781-797. Zhang, Xiang, Gong Cheng, and Yuzhong Qu. "Ontology summarization based on rdf sentence graph." Proceedings of the 16th international conference on World Wide Web. ACM, 2007. Tian, Yuanyuan, Richard A. Hankins, and Jignesh M. Patel. "Efficient aggregation for graph summarization." Proceedings of the 2008 ACM SIGMOD international conference on Management of data. ACM, 2008. Basse, Adrien, et al. "DFS-based frequent graph pattern extraction to characterize the content of RDF Triple Stores." (2010).

Thank you! Any Questions?