Survey of Entity Relationship Extraction Methods in Knowledge Graphs
Entity-relationship extraction has gained more and more attention from researchers as a basis for knowledge graph construction. Entity-relationship extraction can automatically and accurately obtain knowledge from a large amount of data, and represent and store it in a structured form. Therefore, th...
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| Format: | Article |
| Language: | zho |
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Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
2024-03-01
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| Series: | Jisuanji kexue yu tansuo |
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| Online Access: | http://fcst.ceaj.org/fileup/1673-9418/PDF/2305019.pdf |
| _version_ | 1797271478732849152 |
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| author | ZHANG Xishuo, LIU Lin, WANG Hailong, SU Guibin, LIU Jing |
| author_facet | ZHANG Xishuo, LIU Lin, WANG Hailong, SU Guibin, LIU Jing |
| author_sort | ZHANG Xishuo, LIU Lin, WANG Hailong, SU Guibin, LIU Jing |
| collection | DOAJ |
| description | Entity-relationship extraction has gained more and more attention from researchers as a basis for knowledge graph construction. Entity-relationship extraction can automatically and accurately obtain knowledge from a large amount of data, and represent and store it in a structured form. Therefore, the correctness of entity-relationship extraction directly affects the accuracy of knowledge graph construction and the effect of subsequent knowledge graph application. However, for different research hotspots such as complex structure, open domain, multi-language, multi-modal, small sample data, and joint extraction of entity-relationships, the existing entity-relationship extraction methods still have some limitations. Based on the current research hotspots of entity-relationship extraction, this paper tries to categorize entity-relationship extraction into six aspects: complex structure, open domain, multilingual, multimodal, small-sample data, and joint entity-relationship extraction, and categorizes each aspect according to the specific problems and lists out some solutions. Not only the current problems and solutions of each category are systematically sorted out, but the research results of each category are summarized, and the advantages and disadvantages of each method are analyzed in detail from the dimensions of quantitative analysis and qualitative analysis. Finally, the problems to be solved in the current hot areas are summarized, and the future development trend of entity-relationship extraction methods in the knowledge graph is also prospected. |
| first_indexed | 2024-03-07T14:04:12Z |
| format | Article |
| id | doaj.art-a202129a1f0441039b6f28ea22104975 |
| institution | Directory Open Access Journal |
| issn | 1673-9418 |
| language | zho |
| last_indexed | 2024-03-07T14:04:12Z |
| publishDate | 2024-03-01 |
| publisher | Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press |
| record_format | Article |
| series | Jisuanji kexue yu tansuo |
| spelling | doaj.art-a202129a1f0441039b6f28ea221049752024-03-07T02:27:38ZzhoJournal of Computer Engineering and Applications Beijing Co., Ltd., Science PressJisuanji kexue yu tansuo1673-94182024-03-0118357459610.3778/j.issn.1673-9418.2305019Survey of Entity Relationship Extraction Methods in Knowledge GraphsZHANG Xishuo, LIU Lin, WANG Hailong, SU Guibin, LIU Jing01. School of Computer Science and Technology, Inner Mongolia Normal University, Hohhot 010022, China 2. Computer Science Joint Innovation Laboratory, Inner Mongolia Normal University, Hohhot 010022, China 3. Academic Affairs Office, Inner Mongolia Normal University, Hohhot 010022, China 4. Library, Inner Mongolia University, Hohhot 010021, ChinaEntity-relationship extraction has gained more and more attention from researchers as a basis for knowledge graph construction. Entity-relationship extraction can automatically and accurately obtain knowledge from a large amount of data, and represent and store it in a structured form. Therefore, the correctness of entity-relationship extraction directly affects the accuracy of knowledge graph construction and the effect of subsequent knowledge graph application. However, for different research hotspots such as complex structure, open domain, multi-language, multi-modal, small sample data, and joint extraction of entity-relationships, the existing entity-relationship extraction methods still have some limitations. Based on the current research hotspots of entity-relationship extraction, this paper tries to categorize entity-relationship extraction into six aspects: complex structure, open domain, multilingual, multimodal, small-sample data, and joint entity-relationship extraction, and categorizes each aspect according to the specific problems and lists out some solutions. Not only the current problems and solutions of each category are systematically sorted out, but the research results of each category are summarized, and the advantages and disadvantages of each method are analyzed in detail from the dimensions of quantitative analysis and qualitative analysis. Finally, the problems to be solved in the current hot areas are summarized, and the future development trend of entity-relationship extraction methods in the knowledge graph is also prospected.http://fcst.ceaj.org/fileup/1673-9418/PDF/2305019.pdfknowledge graph construction; entity extraction; relationship extraction |
| spellingShingle | ZHANG Xishuo, LIU Lin, WANG Hailong, SU Guibin, LIU Jing Survey of Entity Relationship Extraction Methods in Knowledge Graphs Jisuanji kexue yu tansuo knowledge graph construction; entity extraction; relationship extraction |
| title | Survey of Entity Relationship Extraction Methods in Knowledge Graphs |
| title_full | Survey of Entity Relationship Extraction Methods in Knowledge Graphs |
| title_fullStr | Survey of Entity Relationship Extraction Methods in Knowledge Graphs |
| title_full_unstemmed | Survey of Entity Relationship Extraction Methods in Knowledge Graphs |
| title_short | Survey of Entity Relationship Extraction Methods in Knowledge Graphs |
| title_sort | survey of entity relationship extraction methods in knowledge graphs |
| topic | knowledge graph construction; entity extraction; relationship extraction |
| url | http://fcst.ceaj.org/fileup/1673-9418/PDF/2305019.pdf |
| work_keys_str_mv | AT zhangxishuoliulinwanghailongsuguibinliujing surveyofentityrelationshipextractionmethodsinknowledgegraphs |