Reasoning based on symbolic and parametric knowledge bases: a survey Article Swipe
M. Xu
,
Yang Ning
,
Yongqi Li
,
Jianhao Chen
,
Wen Jiang
,
Yao Xiao
,
Shen Zhou
,
Bailin Pan
,
Zhi-Fan Bao
,
Xin Miao
,
Hyun Kang
,
Ke Sun
,
Tieyun Qian
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2501.01030
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2501.01030
Reasoning is fundamental to human intelligence, and critical for problem-solving, decision-making, and critical thinking. Reasoning refers to drawing new conclusions based on existing knowledge, which can support various applications like clinical diagnosis, basic education, and financial analysis. Though a good number of surveys have been proposed for reviewing reasoning-related methods, none of them has systematically investigated these methods from the viewpoint of their dependent knowledge base. Both the scenarios to which the knowledge bases are applied and their storage formats are significantly different. Hence, investigating reasoning methods from the knowledge base perspective helps us better understand the challenges and future directions. To fill this gap, this paper first classifies the knowledge base into symbolic and parametric ones. The former explicitly stores information in human-readable symbols, and the latter implicitly encodes knowledge within parameters. Then, we provide a comprehensive overview of reasoning methods using symbolic knowledge bases, parametric knowledge bases, and both of them. Finally, we identify the future direction toward enhancing reasoning capabilities to bridge the gap between human and machine intelligence.
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2501.01030
- https://arxiv.org/pdf/2501.01030
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4406033003
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4406033003Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2501.01030Digital Object Identifier
- Title
-
Reasoning based on symbolic and parametric knowledge bases: a surveyWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-01-02Full publication date if available
- Authors
-
M. Xu, Yang Ning, Yongqi Li, Jianhao Chen, Wen Jiang, Yao Xiao, Shen Zhou, Bailin Pan, Zhi-Fan Bao, Xin Miao, Hyun Kang, Ke Sun, Tieyun QianList of authors in order
- Landing page
-
https://arxiv.org/abs/2501.01030Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2501.01030Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2501.01030Direct OA link when available
- Concepts
-
Computer science, Parametric statistics, Knowledge management, Data science, Mathematics, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4406033003 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2501.01030 |
| ids.doi | https://doi.org/10.48550/arxiv.2501.01030 |
| ids.openalex | https://openalex.org/W4406033003 |
| fwci | |
| type | preprint |
| title | Reasoning based on symbolic and parametric knowledge bases: a survey |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10215 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9829999804496765 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1702 |
| topics[0].subfield.display_name | Artificial Intelligence |
| topics[0].display_name | Semantic Web and Ontologies |
| topics[1].id | https://openalex.org/T10181 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9416999816894531 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1702 |
| topics[1].subfield.display_name | Artificial Intelligence |
| topics[1].display_name | Natural Language Processing Techniques |
| topics[2].id | https://openalex.org/T13083 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.902999997138977 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1702 |
| topics[2].subfield.display_name | Artificial Intelligence |
| topics[2].display_name | Advanced Text Analysis Techniques |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.5375366806983948 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C117251300 |
| concepts[1].level | 2 |
| concepts[1].score | 0.46662840247154236 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q1849855 |
| concepts[1].display_name | Parametric statistics |
| concepts[2].id | https://openalex.org/C56739046 |
| concepts[2].level | 1 |
| concepts[2].score | 0.41108617186546326 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q192060 |
| concepts[2].display_name | Knowledge management |
| concepts[3].id | https://openalex.org/C2522767166 |
| concepts[3].level | 1 |
| concepts[3].score | 0.3942829668521881 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q2374463 |
| concepts[3].display_name | Data science |
| concepts[4].id | https://openalex.org/C33923547 |
| concepts[4].level | 0 |
| concepts[4].score | 0.20631375908851624 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[4].display_name | Mathematics |
| concepts[5].id | https://openalex.org/C105795698 |
| concepts[5].level | 1 |
| concepts[5].score | 0.12327343225479126 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[5].display_name | Statistics |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.5375366806983948 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/parametric-statistics |
| keywords[1].score | 0.46662840247154236 |
| keywords[1].display_name | Parametric statistics |
| keywords[2].id | https://openalex.org/keywords/knowledge-management |
| keywords[2].score | 0.41108617186546326 |
| keywords[2].display_name | Knowledge management |
| keywords[3].id | https://openalex.org/keywords/data-science |
| keywords[3].score | 0.3942829668521881 |
| keywords[3].display_name | Data science |
| keywords[4].id | https://openalex.org/keywords/mathematics |
| keywords[4].score | 0.20631375908851624 |
| keywords[4].display_name | Mathematics |
| keywords[5].id | https://openalex.org/keywords/statistics |
| keywords[5].score | 0.12327343225479126 |
| keywords[5].display_name | Statistics |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2501.01030 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/2501.01030 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | text |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/2501.01030 |
| locations[1].id | doi:10.48550/arxiv.2501.01030 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400194 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | arXiv (Cornell University) |
| locations[1].source.host_organization | https://openalex.org/I205783295 |
| locations[1].source.host_organization_name | Cornell University |
| locations[1].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://doi.org/10.48550/arxiv.2501.01030 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5100607379 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-0718-8416 |
| authorships[0].author.display_name | M. Xu |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Xu, Mayi |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5070406375 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-6877-9231 |
| authorships[1].author.display_name | Yang Ning |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Ning, Yunfeng |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5083885823 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Yongqi Li |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Li, Yongqi |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5101728579 |
| authorships[3].author.orcid | https://orcid.org/0009-0006-4363-0549 |
| authorships[3].author.display_name | Jianhao Chen |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Chen, Jianhao |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5090210760 |
| authorships[4].author.orcid | https://orcid.org/0000-0001-9154-633X |
| authorships[4].author.display_name | Wen Jiang |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Wen, Jintao |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5100770186 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-4999-9252 |
| authorships[5].author.display_name | Yao Xiao |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Xiao, Yao |
| authorships[5].is_corresponding | False |
| authorships[6].author.id | https://openalex.org/A5101299664 |
| authorships[6].author.orcid | |
| authorships[6].author.display_name | Shen Zhou |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Zhou, Shen |
| authorships[6].is_corresponding | False |
| authorships[7].author.id | https://openalex.org/A5054150383 |
| authorships[7].author.orcid | https://orcid.org/0000-0002-2563-8997 |
| authorships[7].author.display_name | Bailin Pan |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Pan, Birong |
| authorships[7].is_corresponding | False |
| authorships[8].author.id | https://openalex.org/A5051565041 |
| authorships[8].author.orcid | |
| authorships[8].author.display_name | Zhi-Fan Bao |
| authorships[8].author_position | middle |
| authorships[8].raw_author_name | Bao, Zepeng |
| authorships[8].is_corresponding | False |
| authorships[9].author.id | https://openalex.org/A5100729108 |
| authorships[9].author.orcid | https://orcid.org/0000-0002-3208-630X |
| authorships[9].author.display_name | Xin Miao |
| authorships[9].author_position | middle |
| authorships[9].raw_author_name | Miao, Xin |
| authorships[9].is_corresponding | False |
| authorships[10].author.id | https://openalex.org/A5073042222 |
| authorships[10].author.orcid | |
| authorships[10].author.display_name | Hyun Kang |
| authorships[10].author_position | middle |
| authorships[10].raw_author_name | Kang, Hankun |
| authorships[10].is_corresponding | False |
| authorships[11].author.id | https://openalex.org/A5100408895 |
| authorships[11].author.orcid | https://orcid.org/0000-0001-6234-4878 |
| authorships[11].author.display_name | Ke Sun |
| authorships[11].author_position | middle |
| authorships[11].raw_author_name | Sun, Ke |
| authorships[11].is_corresponding | False |
| authorships[12].author.id | https://openalex.org/A5040759280 |
| authorships[12].author.orcid | https://orcid.org/0000-0003-4667-5794 |
| authorships[12].author.display_name | Tieyun Qian |
| authorships[12].author_position | last |
| authorships[12].raw_author_name | Qian, Tieyun |
| authorships[12].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2501.01030 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Reasoning based on symbolic and parametric knowledge bases: a survey |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T10215 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9829999804496765 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1702 |
| primary_topic.subfield.display_name | Artificial Intelligence |
| primary_topic.display_name | Semantic Web and Ontologies |
| related_works | https://openalex.org/W4391375266, https://openalex.org/W2899084033, https://openalex.org/W2748952813, https://openalex.org/W2390279801, https://openalex.org/W4391913857, https://openalex.org/W2358668433, https://openalex.org/W4396701345, https://openalex.org/W2376932109, https://openalex.org/W2001405890, https://openalex.org/W4396696052 |
| cited_by_count | 0 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:2501.01030 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/2501.01030 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | text |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/2501.01030 |
| primary_location.id | pmh:oai:arXiv.org:2501.01030 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2501.01030 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | text |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2501.01030 |
| publication_date | 2025-01-02 |
| publication_year | 2025 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 38, 136 |
| abstract_inverted_index.To | 101 |
| abstract_inverted_index.in | 122 |
| abstract_inverted_index.is | 1 |
| abstract_inverted_index.of | 41, 51, 61, 139, 151 |
| abstract_inverted_index.on | 21 |
| abstract_inverted_index.to | 3, 16, 69, 163 |
| abstract_inverted_index.us | 93 |
| abstract_inverted_index.we | 134, 154 |
| abstract_inverted_index.The | 117 |
| abstract_inverted_index.and | 6, 11, 34, 76, 98, 114, 125, 149, 169 |
| abstract_inverted_index.are | 74, 80 |
| abstract_inverted_index.can | 25 |
| abstract_inverted_index.for | 8, 46 |
| abstract_inverted_index.gap | 166 |
| abstract_inverted_index.has | 53 |
| abstract_inverted_index.new | 18 |
| abstract_inverted_index.the | 59, 67, 71, 88, 96, 109, 126, 156, 165 |
| abstract_inverted_index.Both | 66 |
| abstract_inverted_index.base | 90, 111 |
| abstract_inverted_index.been | 44 |
| abstract_inverted_index.both | 150 |
| abstract_inverted_index.fill | 102 |
| abstract_inverted_index.from | 58, 87 |
| abstract_inverted_index.gap, | 104 |
| abstract_inverted_index.good | 39 |
| abstract_inverted_index.have | 43 |
| abstract_inverted_index.into | 112 |
| abstract_inverted_index.like | 29 |
| abstract_inverted_index.none | 50 |
| abstract_inverted_index.them | 52 |
| abstract_inverted_index.this | 103, 105 |
| abstract_inverted_index.Then, | 133 |
| abstract_inverted_index.base. | 65 |
| abstract_inverted_index.based | 20 |
| abstract_inverted_index.bases | 73 |
| abstract_inverted_index.basic | 32 |
| abstract_inverted_index.first | 107 |
| abstract_inverted_index.helps | 92 |
| abstract_inverted_index.human | 4, 168 |
| abstract_inverted_index.ones. | 116 |
| abstract_inverted_index.paper | 106 |
| abstract_inverted_index.their | 62, 77 |
| abstract_inverted_index.them. | 152 |
| abstract_inverted_index.these | 56 |
| abstract_inverted_index.using | 142 |
| abstract_inverted_index.which | 24, 70 |
| abstract_inverted_index.Hence, | 83 |
| abstract_inverted_index.Though | 37 |
| abstract_inverted_index.bases, | 145, 148 |
| abstract_inverted_index.better | 94 |
| abstract_inverted_index.bridge | 164 |
| abstract_inverted_index.former | 118 |
| abstract_inverted_index.future | 99, 157 |
| abstract_inverted_index.latter | 127 |
| abstract_inverted_index.number | 40 |
| abstract_inverted_index.refers | 15 |
| abstract_inverted_index.stores | 120 |
| abstract_inverted_index.toward | 159 |
| abstract_inverted_index.within | 131 |
| abstract_inverted_index.applied | 75 |
| abstract_inverted_index.between | 167 |
| abstract_inverted_index.drawing | 17 |
| abstract_inverted_index.encodes | 129 |
| abstract_inverted_index.formats | 79 |
| abstract_inverted_index.machine | 170 |
| abstract_inverted_index.methods | 57, 86, 141 |
| abstract_inverted_index.provide | 135 |
| abstract_inverted_index.storage | 78 |
| abstract_inverted_index.support | 26 |
| abstract_inverted_index.surveys | 42 |
| abstract_inverted_index.various | 27 |
| abstract_inverted_index.Finally, | 153 |
| abstract_inverted_index.clinical | 30 |
| abstract_inverted_index.critical | 7, 12 |
| abstract_inverted_index.existing | 22 |
| abstract_inverted_index.identify | 155 |
| abstract_inverted_index.methods, | 49 |
| abstract_inverted_index.overview | 138 |
| abstract_inverted_index.proposed | 45 |
| abstract_inverted_index.symbolic | 113, 143 |
| abstract_inverted_index.symbols, | 124 |
| abstract_inverted_index.Reasoning | 0, 14 |
| abstract_inverted_index.analysis. | 36 |
| abstract_inverted_index.dependent | 63 |
| abstract_inverted_index.direction | 158 |
| abstract_inverted_index.enhancing | 160 |
| abstract_inverted_index.financial | 35 |
| abstract_inverted_index.knowledge | 64, 72, 89, 110, 130, 144, 147 |
| abstract_inverted_index.reasoning | 85, 140, 161 |
| abstract_inverted_index.reviewing | 47 |
| abstract_inverted_index.scenarios | 68 |
| abstract_inverted_index.thinking. | 13 |
| abstract_inverted_index.viewpoint | 60 |
| abstract_inverted_index.challenges | 97 |
| abstract_inverted_index.classifies | 108 |
| abstract_inverted_index.diagnosis, | 31 |
| abstract_inverted_index.different. | 82 |
| abstract_inverted_index.education, | 33 |
| abstract_inverted_index.explicitly | 119 |
| abstract_inverted_index.implicitly | 128 |
| abstract_inverted_index.knowledge, | 23 |
| abstract_inverted_index.parametric | 115, 146 |
| abstract_inverted_index.understand | 95 |
| abstract_inverted_index.conclusions | 19 |
| abstract_inverted_index.directions. | 100 |
| abstract_inverted_index.fundamental | 2 |
| abstract_inverted_index.information | 121 |
| abstract_inverted_index.parameters. | 132 |
| abstract_inverted_index.perspective | 91 |
| abstract_inverted_index.applications | 28 |
| abstract_inverted_index.capabilities | 162 |
| abstract_inverted_index.investigated | 55 |
| abstract_inverted_index.comprehensive | 137 |
| abstract_inverted_index.intelligence, | 5 |
| abstract_inverted_index.intelligence. | 171 |
| abstract_inverted_index.investigating | 84 |
| abstract_inverted_index.significantly | 81 |
| abstract_inverted_index.human-readable | 123 |
| abstract_inverted_index.systematically | 54 |
| abstract_inverted_index.decision-making, | 10 |
| abstract_inverted_index.problem-solving, | 9 |
| abstract_inverted_index.reasoning-related | 48 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 13 |
| citation_normalized_percentile |