Fw: Programme of EEKE2021
Fei Shu
Programme
1st Keynote: From Wikis to Knowledge Graphs: Approaches and Challenges beyond DBpedia and YAGO
Abstract: Wikipedia was among the first sources to be identified for automatic knowledge graph construction. DBpedia and YAGO, two of the most widely used public knowledge graphs, perform knowledge extraction from Wikipedia by following the "one entity per Wiki page" paradigm. Thus, the resulting graphs are naturally limited by the coverage of Wikipedia, and they inherit many biases from it. In my talk, I will introduce recent alternatives for creating knowledge graphs from Wikis, in particular DBkWik and CaLiGraph, which use different approaches for identifying entities, and I will point out several challenges that exist off the beaten path of the "one entity per Wiki page" approaches.
Dr.
Heiko Paulheim is a professor for Data Science at the University of Mannheim, Germany. His research focuses on the construction and usage of large-scale knowledge graphs. He explores methods for generating those knowledge graphs
from various sources (such as Wikis and other structured Web sites or parts thereof), as well as techniques for automatically refining those graphs by inferring missing knowledge or finding errors by means of heuristic inference or machine learning. Moreover,
he takes a holistic view on knowledge graph construction and refinement by trying to explicate and leverage meta-knowledge on the knowledge construction process and lifecycle. From an application perspective, he analyses and explores the usage of knowledge
graphs to improve the performance of different knowledge-intensive tasks. Here, he has developed methods for exploiting public knowledge graphs as background knowledge in data mining tasks, both using symbolic and subsymbolic methods, most notably RDF2vec.
Heiko holds a PhD from the Technical University of Darmstadt. (http://www.heikopaulheim.com/)
2nd Keynote: Entity Summarization: Where We Are and What Lies Ahead?
Abstract: Semantic data such as knowledge graphs, describing entities with property values, are increasingly available on the Web. A large number of property values describing an entity may overload users with excessive amounts of information. One solution is to generate a summary (e.g., a small subset of key property values) for entity descriptions to satisfy users' information needs efficiently and effectively. This research topic, termed Entity Summarization, has received considerable attention in the past decade. In this talk, I will review existing methods and evaluation efforts on entity summarization. I will categorize existing methods by presenting a hierarchy of technical features that have been incorporated, including generic, domain-specific, and task-specific features. I will show various frameworks for combining multiple features to assemble a full entity summarizer, including graph-based models, grouping, re-ranking, and combinatorial optimization. I will particularly highlight some pioneering deep learning based methods. Finally, I will discuss limitations of existing methods and, based on that, I will suggest several directions for future research.
Dr.
Gong Cheng is an associate professor at the Department of Computer Science and Technology, Nanjing University. He has been conducting research in Semantic Web and knowledge graphs for intelligent software systems. His research
interests include semantic search, data summarization, and question answering. His research has been published at WWW, ISWC, TKDE, etc., and has received or been nominated for 5 best paper awards. He was a Posters & Demos co-chair of ISWC 2019. (http://ws.nju.edu.cn/wiki/Gong
Cheng)
Sessions
The workshop will be held on Sept 30, 2021 (Beijing Time), and specific activities include keynotes, paper presentations and a poster session.
| 15:20-15:30 | Connection setup: we will provide details | ||
|---|---|---|---|
| 15:30-15:40 | Introduction  |
Co-Chairs of EEKE2021 (Chengzhi Zhang, Philipp Mayr, Wei Lu, Yi Zhang) | |
| 15:40-16:40 | Keynote 1: From Wikis to Knowledge Graphs: Approaches and Challenges beyond DBpedia and YAGO
|
Heiko Paulheim | Chair: Philipp Mayr |
| 16:40-17:30 | Session 1: Entity Extraction and Application | Chair: Philipp Mayr | |
| 16:40-17:00 | ANEA: Automated (Named) Entity Annotation for German Domain-Specific Texts
|
Anastasia Zhukova, Felix Hamborg and Bela Gipp | |
| 17:00-17:15 | Joint Entity and Relation Extraction from Scientific Documents: Role of Linguistic Information and Entity Types
|
Santosh Tokala Yaswanth Sri Sai, Prantika Chakraborty, Sudakshina Dutta, Debarshi Kumar Sanyal and Partha Pratim Das | |
| 17:15-17:30 | Classification of URLs Citing Research Artifacts in Scholarly Documents based on Distributed Representations
|
Masaya Tsunokake and Shigeki Matsubara | |
| 17:30-18:30 | Break | ||
| 18:30-19:20 | Session 2: Keyword Exaction and Applicaiton | Chair: Yingyi Zhang | |
| 18:30-18:50 | Design and Implementation of Keyphrase Extraction Engine for Chinese Scientific Literature
|
Liangping Ding, Zhixiong Zhang, Huan Liu and Yang Zhao | |
| 18:50-19:05 | Keyword Extraction and Technology Entity Extraction for Disruptive Technology Policy Texts
|
Aofei Chang, Bolin Hua and Dahai Yu | |
| 19:05-19:20 | Extracting Domain Entities from Scientific Papers Leveraging Author Keywords
|
Jiabin Peng and Guo Chen | |
| 19:20-20:20 | Keynote 2: Entity Summarization: Where We Are and What Lies Ahead?
|
Gong Cheng | Chair: Chengzhi Zhang |
| 20:20-20:30 | Break | ||
| 20:30-21:20 | Session 3: Knowledge Graph and Application | Chair:Haihua Chen | |
| 20:30-20:50 | Detecting Cross-Language Plagiarism using Open Knowledge Graphs
|
Johannes Stegmüller, Fabian Bauer-Marquart, Norman Meuschke, Terry Ruas, Moritz Schubotz and Bela Gipp | |
| 20:50-21:05 | A PICO-based Knowledge Graph for Representing Clinical Evidence
|
Yongmei Bai, Huage Sun and Jian Du | |
| 21:05-21:20 | A knowledge graph completion model integrating entity description and network structure
|
Chuanming Yu, Zhengang Zhang and Lu An | |
| 21:20-22:30 | Session 4: Poster/ Greeting Notes of EEKE2021 | Chair: Yi Zhang | |
| 21:20-22:20 | The correlation between content novelty and scientific impact  |
Shiyun Wang, Jin Mao and Yaxue Ma | |
| 21:20-22:20 | Automatic Generation of Research Highlights from Scientific Abstracts
|
Tohida Rehman, Debarshi Kumar Sanyal, Samiran Chattopadhyay, Plaban Kumar Bhowmick and Partha Pratim Das | |
| 21:20-22:20 | Differential Analysis on Performance of Scientific Research Teams based on Analysis of the Popularity Evolution of Entities
|
Fang Tan, Tongyang Zhang and Jian Xu | |
| 21:20-22:20 | Research on extraction of thesis research conclusion sentences in academic literature
|
Litao Lin, Dongbo Wang and Si Shen | |
| 21:20-22:20 | Topic Evolution Path and Semantic Relationship Discovery Based on Patent Entity Relationship
|
Jinzhu Zhang and Linqi Jiang | |
| 21:20-22:20 | Bureau for Rapid Annotation Tool: Collaboration can do More over Variety-oriented Annotations
|
Wang Zheng and Xu Shuo | |
| 22:20-22:30 | Greeting Notes of EEKE2021 | Co-Chairs of EEKE2021 (Chengzhi Zhang, Philipp Mayr, Wei Lu, Yi Zhang) | |
| 22:30 | End of workshop | ||
| Co-Chairs of EEKE2021 (Chengzhi Zhang, Philipp Mayr, Wei Lu, Yi Zhang) |