Author Archives: 토니아빠

Global Textual Relation Embedding for Relational Understanding Zhiyu Chen, Hanwen Zha, Honglei Liu, Wenhu Chen, Xifeng Yan, and Yu Su https://www.aclweb.org/anthology/P19-1127.pdf Abstract Pre-trained embeddings such as word embeddings and sentence embeddings are fundamental tools facilitating a wide range of downstream NLP tasks. In this work, we investigate how to learn a general-purpose embedding of textual…더

Low-Dimensional Hyperbolic Knowledge Graph Embeddings (2020) Ines Chami1∗, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi and Christopher Re´ https://www.aclweb.org/anthology/2020.acl-main.617.pdf https://github.com/HazyResearch/KGEmb Abstract Knowledge graph (KG) embeddings learn lowdimensional representations of entities and relations to predict missing facts. KGs often exhibit hierarchical and logical patterns which must be preserved in the embedding space. For hierarchical data,…더

graph2vec: Learning Distributed Representations of Graphs (2017.7) Annamalai Narayanan, Mahinthan Chandramohan, Rajasekar Venkatesan, Lihui Chen, Yang Liu and Shantanu Jaiswal https://arxiv.org/pdf/1707.05005.pdf ABSTRACT Recent works on representation learning for graph structured data predominantly focus on learning distributed representations of graph substructures such as nodes and subgraphs. However, many graph analytics tasks such as graph classification and…더

node2vec: Scalable Feature Learning for Networks (2016) Aditya Grover, Jure Leskovec https://arxiv.org/pdf/1607.00653.pdf ABSTRACT Prediction tasks over nodes and edges in networks require careful effort in engineering features used by learning algorithms. Recent research in the broader field of representation learning has led to significant progress in automating prediction by learning the features themselves. However, present…더

Sentence and Word Embedding Employed in Open Question-Answering (2018) Marek Medved and Aleš Horák https://www.scitepress.org/papers/2018/65959/65959.pdf Abstract: The Automatic Question Answering, or AQA, system is a representative of open domain QA systems, where the answer selection process leans on syntactic and semantic similarities between the question and the answering text snippets. Such approach is specifically oriented…더

Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings (2020) Apoorv Saxena∗ Aditay Tripathi∗ Partha Talukdar file://Improving_Multi-hop_Question_Answering_over_Knowle.pdf Abstract Knowledge Graphs (KG) are multi-relational graphs consisting of entities as nodes and relations among them as typed edges. Goal of the Question Answering over KG (KGQA) task is to answer natural language queries posed over…더

Construction of an Industrial Knowledge Graph for Unstructured Chinese Text Learning (May 2019) Mingxiong Zhao , Han Wang, Jin Guo, Di Liu, Cheng Xie * , Qing Liu and Zhibo Cheng https://www.mdpi.com/2076-3417/9/13/2720/pdf Abstract: The industrial 4.0 era is the fourth industrial revolution and is characterized by network penetration; therefore, traditional manufacturing and value creation will…더

A Survey on Knowledge Graphs: Representation, Acquisition and Applications (2020.8) Shaoxiong Ji, Shirui Pan, Erik Cambria, Senior Member, IEEE,Pekka Marttinen, Philip S. Yu, Life Fellow, IEEE, https://arxiv.org/pdf/2002.00388.pdf Abstract Human knowledge provides a formal understanding of the world. Knowledge graphs that represent structural relations between entities have become an increasingly popular research direction towards cognition and…더

AgensGraph 는 Postgresql 10 기반으로 개발되었습니다. 그래서 systemctl start/stop/restart 등의 명령어도 postgres service 파일과 유사하게 만들면 됩니다.참고문서: CentOS 7 에 Postgresql Service 설정하기 Ubuntu(Linux) 의 경우 service 정의 파일의 위치는 /etc/systemd/system 입니다.앞에 agensgraph.service 파일을 /etc/systemd/system 위치에 생성합니다. 이후 systemctl 을 통해 service 를 enable 시키고, start/stop 를 테스트합니다.참고문서: Ubuntu 16.04 System Service 등록하기 (** Ubuntu…더