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Book ChapterDOI

CN-DBpedia: A Never-Ending Chinese Knowledge Extraction System

TLDR
A never-ending Chinese Knowledge extraction system, CN-DBpedia, which can automatically generate a knowledge base that is of ever-increasing in size and constantly updated, and reduces the human costs by reusing the ontology of existing knowledge bases and building an end-to-end facts extraction model.
Abstract
Great efforts have been dedicated to harvesting knowledge bases from online encyclopedias These knowledge bases play important roles in enabling machines to understand texts However, most current knowledge bases are in English and non-English knowledge bases, especially Chinese ones, are still very rare Many previous systems that extract knowledge from online encyclopedias, although are applicable for building a Chinese knowledge base, still suffer from two challenges The first is that it requires great human efforts to construct an ontology and build a supervised knowledge extraction model The second is that the update frequency of knowledge bases is very slow To solve these challenges, we propose a never-ending Chinese Knowledge extraction system, CN-DBpedia, which can automatically generate a knowledge base that is of ever-increasing in size and constantly updated Specially, we reduce the human costs by reusing the ontology of existing knowledge bases and building an end-to-end facts extraction model We further propose a smart active update strategy to keep the freshness of our knowledge base with little human costs The 164 million API calls of the published services justify the success of our system

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Citations
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Journal ArticleDOI

K-BERT: Enabling Language Representation with Knowledge Graph

TL;DR: This work proposes a knowledge-enabled language representation model (K-BERT) with knowledge graphs (KGs), in which triples are injected into the sentences as domain knowledge, which significantly outperforms BERT and reveals promising results in twelve NLP tasks.
Journal ArticleDOI

A survey on knowledge graph-based recommender systems

TL;DR: In this paper, the authors provide a focused survey on KG-based recommender system via a holistic perspective of both technologies and applications, and present their opinions on the prospects of KG based recommender systems and suggest some future research directions.
Journal ArticleDOI

A Survey on Knowledge Graph-Based Recommender Systems

TL;DR: In this paper , the authors conduct a systematical survey of knowledge graph-based recommender systems and propose several potential research directions in this field, focusing on how the papers utilize the knowledge graph for accurate and explainable recommendation.
Proceedings ArticleDOI

Entity-Duet Neural Ranking: Understanding the Role of Knowledge Graph Semantics in Neural Information Retrieval

TL;DR: The Entity-Duet Neural Ranking Model (EDRM) as mentioned in this paper introduces knowledge graphs to neural search systems, where the semantics from knowledge graphs are integrated in the distributed representations of their entities, while the ranking is conducted by interaction-based neural ranking networks.
Journal ArticleDOI

Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks

TL;DR: Wang et al. as mentioned in this paper designed a novel event-based meta-schema to characterize the semantic relatedness of social events and then built an event based heterogeneous information network (HIN) integrating information from external knowledge base.
References
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Book ChapterDOI

DBpedia: a nucleus for a web of open data

TL;DR: The extraction of the DBpedia datasets is described, and how the resulting information is published on the Web for human-andmachine-consumption and how DBpedia could serve as a nucleus for an emerging Web of open data.
Proceedings ArticleDOI

Freebase: a collaboratively created graph database for structuring human knowledge

TL;DR: MQL provides an easy-to-use object-oriented interface to the tuple data in Freebase and is designed to facilitate the creation of collaborative, Web-based data-oriented applications.
Proceedings ArticleDOI

Yago: a core of semantic knowledge

TL;DR: YAGO as discussed by the authors is a light-weight and extensible ontology with high coverage and quality, which includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as HASONEPRIZE).
Journal ArticleDOI

DBpedia - A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia

TL;DR: An overview of the DBpedia community project is given, including its architecture, technical implementation, maintenance, internationalisation, usage statistics and applications, including DBpedia one of the central interlinking hubs in the Linked Open Data (LOD) cloud.
Book ChapterDOI

Zhishi.me: weaving chinese linking open data

TL;DR: This paper presents Zhishi.me, the first effort to publish large scale Chinese semantic data and link them together as a Chinese LOD (CLOD), and identifies important structural features in three largest Chinese encyclopedia sites for extraction and proposes several data-level mapping strategies for automatic link discovery.
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