Mining Approximate Acyclic Schemes from Relations Article Swipe
Batya Kenig
,
Pranay Mundra
,
Guna Prasad
,
Babak Salimi
,
Dan Suciu
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1911.12933
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1911.12933
Acyclic schemes have numerous applications in databases and in machine learning, such as improved design, more efficient storage, and increased performance for queries and machine learning algorithms. Multivalued dependencies (MVDs) are the building blocks of acyclic schemes. The discovery from data of both MVDs and acyclic schemes is more challenging than other forms of data dependencies, such as Functional Dependencies, because these dependencies do not hold on subsets of data, and because they are very sensitive to noise in the data; for example a single wrong or missing tuple may invalidate the schema. In this paper we present Maimon, a system for discovering approximate acyclic schemes and MVDs from data. We give a principled definition of approximation, by using notions from information theory, then describe the two components of Maimon: mining for approximate MVDs, then reconstructing acyclic schemes from approximate MVDs. We conduct an experimental evaluation of Maimon on 20 real-world datasets, and show that it can scale up to 1M rows, and up to 30 columns.
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1911.12933
- https://arxiv.org/pdf/1911.12933
- OA Status
- green
- References
- 40
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2990581997
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2990581997Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.1911.12933Digital Object Identifier
- Title
-
Mining Approximate Acyclic Schemes from RelationsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-11-29Full publication date if available
- Authors
-
Batya Kenig, Pranay Mundra, Guna Prasad, Babak Salimi, Dan SuciuList of authors in order
- Landing page
-
https://arxiv.org/abs/1911.12933Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1911.12933Direct 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/1911.12933Direct OA link when available
- Concepts
-
Computer science, Tuple, Schema (genetic algorithms), Row, Directed acyclic graph, Theoretical computer science, Functional dependency, Algorithm, Relational database, Data mining, Information retrieval, Mathematics, Database, Discrete mathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
40Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2990581997 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.1911.12933 |
| ids.doi | https://doi.org/10.48550/arxiv.1911.12933 |
| ids.mag | 2990581997 |
| ids.openalex | https://openalex.org/W2990581997 |
| fwci | |
| type | preprint |
| title | Mining Approximate Acyclic Schemes from Relations |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T11719 |
| topics[0].field.id | https://openalex.org/fields/18 |
| topics[0].field.display_name | Decision Sciences |
| topics[0].score | 0.9993000030517578 |
| topics[0].domain.id | https://openalex.org/domains/2 |
| topics[0].domain.display_name | Social Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1803 |
| topics[0].subfield.display_name | Management Science and Operations Research |
| topics[0].display_name | Data Quality and Management |
| topics[1].id | https://openalex.org/T10317 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9986000061035156 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1705 |
| topics[1].subfield.display_name | Computer Networks and Communications |
| topics[1].display_name | Advanced Database Systems and Queries |
| topics[2].id | https://openalex.org/T10538 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9977999925613403 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1710 |
| topics[2].subfield.display_name | Information Systems |
| topics[2].display_name | Data Mining Algorithms and Applications |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.7427133917808533 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C118930307 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7250005006790161 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q600590 |
| concepts[1].display_name | Tuple |
| concepts[2].id | https://openalex.org/C52146309 |
| concepts[2].level | 2 |
| concepts[2].score | 0.6100433468818665 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q7431116 |
| concepts[2].display_name | Schema (genetic algorithms) |
| concepts[3].id | https://openalex.org/C135598885 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5998475551605225 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1366302 |
| concepts[3].display_name | Row |
| concepts[4].id | https://openalex.org/C74197172 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5414069294929504 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1195339 |
| concepts[4].display_name | Directed acyclic graph |
| concepts[5].id | https://openalex.org/C80444323 |
| concepts[5].level | 1 |
| concepts[5].score | 0.5208247900009155 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q2878974 |
| concepts[5].display_name | Theoretical computer science |
| concepts[6].id | https://openalex.org/C26320393 |
| concepts[6].level | 3 |
| concepts[6].score | 0.4472983181476593 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q597053 |
| concepts[6].display_name | Functional dependency |
| concepts[7].id | https://openalex.org/C11413529 |
| concepts[7].level | 1 |
| concepts[7].score | 0.32258936762809753 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[7].display_name | Algorithm |
| concepts[8].id | https://openalex.org/C5655090 |
| concepts[8].level | 2 |
| concepts[8].score | 0.32072699069976807 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q192588 |
| concepts[8].display_name | Relational database |
| concepts[9].id | https://openalex.org/C124101348 |
| concepts[9].level | 1 |
| concepts[9].score | 0.26368993520736694 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[9].display_name | Data mining |
| concepts[10].id | https://openalex.org/C23123220 |
| concepts[10].level | 1 |
| concepts[10].score | 0.2127338945865631 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q816826 |
| concepts[10].display_name | Information retrieval |
| concepts[11].id | https://openalex.org/C33923547 |
| concepts[11].level | 0 |
| concepts[11].score | 0.20434901118278503 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[11].display_name | Mathematics |
| concepts[12].id | https://openalex.org/C77088390 |
| concepts[12].level | 1 |
| concepts[12].score | 0.13312968611717224 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q8513 |
| concepts[12].display_name | Database |
| concepts[13].id | https://openalex.org/C118615104 |
| concepts[13].level | 1 |
| concepts[13].score | 0.120303213596344 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q121416 |
| concepts[13].display_name | Discrete mathematics |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.7427133917808533 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/tuple |
| keywords[1].score | 0.7250005006790161 |
| keywords[1].display_name | Tuple |
| keywords[2].id | https://openalex.org/keywords/schema |
| keywords[2].score | 0.6100433468818665 |
| keywords[2].display_name | Schema (genetic algorithms) |
| keywords[3].id | https://openalex.org/keywords/row |
| keywords[3].score | 0.5998475551605225 |
| keywords[3].display_name | Row |
| keywords[4].id | https://openalex.org/keywords/directed-acyclic-graph |
| keywords[4].score | 0.5414069294929504 |
| keywords[4].display_name | Directed acyclic graph |
| keywords[5].id | https://openalex.org/keywords/theoretical-computer-science |
| keywords[5].score | 0.5208247900009155 |
| keywords[5].display_name | Theoretical computer science |
| keywords[6].id | https://openalex.org/keywords/functional-dependency |
| keywords[6].score | 0.4472983181476593 |
| keywords[6].display_name | Functional dependency |
| keywords[7].id | https://openalex.org/keywords/algorithm |
| keywords[7].score | 0.32258936762809753 |
| keywords[7].display_name | Algorithm |
| keywords[8].id | https://openalex.org/keywords/relational-database |
| keywords[8].score | 0.32072699069976807 |
| keywords[8].display_name | Relational database |
| keywords[9].id | https://openalex.org/keywords/data-mining |
| keywords[9].score | 0.26368993520736694 |
| keywords[9].display_name | Data mining |
| keywords[10].id | https://openalex.org/keywords/information-retrieval |
| keywords[10].score | 0.2127338945865631 |
| keywords[10].display_name | Information retrieval |
| keywords[11].id | https://openalex.org/keywords/mathematics |
| keywords[11].score | 0.20434901118278503 |
| keywords[11].display_name | Mathematics |
| keywords[12].id | https://openalex.org/keywords/database |
| keywords[12].score | 0.13312968611717224 |
| keywords[12].display_name | Database |
| keywords[13].id | https://openalex.org/keywords/discrete-mathematics |
| keywords[13].score | 0.120303213596344 |
| keywords[13].display_name | Discrete mathematics |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:1911.12933 |
| 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/1911.12933 |
| 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/1911.12933 |
| locations[1].id | doi:10.48550/arxiv.1911.12933 |
| 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.1911.12933 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5047636495 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-6349-128X |
| authorships[0].author.display_name | Batya Kenig |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Batya Kenig |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5067630615 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-6727-1505 |
| authorships[1].author.display_name | Pranay Mundra |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Pranay Mundra |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5006887650 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Guna Prasad |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Guna Prasad |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5103209063 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-2485-9533 |
| authorships[3].author.display_name | Babak Salimi |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Babak Salimi |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5048204602 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-4144-0868 |
| authorships[4].author.display_name | Dan Suciu |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Dan Suciu |
| authorships[4].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/1911.12933 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Mining Approximate Acyclic Schemes from Relations |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T11719 |
| primary_topic.field.id | https://openalex.org/fields/18 |
| primary_topic.field.display_name | Decision Sciences |
| primary_topic.score | 0.9993000030517578 |
| primary_topic.domain.id | https://openalex.org/domains/2 |
| primary_topic.domain.display_name | Social Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1803 |
| primary_topic.subfield.display_name | Management Science and Operations Research |
| primary_topic.display_name | Data Quality and Management |
| related_works | https://openalex.org/W2116767780, https://openalex.org/W165346131, https://openalex.org/W1594511838, https://openalex.org/W4285259755, https://openalex.org/W119841348, https://openalex.org/W2171948294, https://openalex.org/W2039445786, https://openalex.org/W2185054849, https://openalex.org/W2952114617, https://openalex.org/W316061934 |
| cited_by_count | 0 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:1911.12933 |
| 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/1911.12933 |
| 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/1911.12933 |
| primary_location.id | pmh:oai:arXiv.org:1911.12933 |
| 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/1911.12933 |
| 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/1911.12933 |
| publication_date | 2019-11-29 |
| publication_year | 2019 |
| referenced_works | https://openalex.org/W2143182259, https://openalex.org/W2798658665, https://openalex.org/W2284514301, https://openalex.org/W2110810394, https://openalex.org/W1978544932, https://openalex.org/W2997485842, https://openalex.org/W2023663289, https://openalex.org/W2012628629, https://openalex.org/W1968137129, https://openalex.org/W2948085204, https://openalex.org/W2166549982, https://openalex.org/W2963560792, https://openalex.org/W2039610696, https://openalex.org/W2612955371, https://openalex.org/W2029570660, https://openalex.org/W2439326083, https://openalex.org/W2532748481, https://openalex.org/W2038254774, https://openalex.org/W2125223317, https://openalex.org/W1502954553, https://openalex.org/W1994962776, https://openalex.org/W2099159152, https://openalex.org/W2013026082, https://openalex.org/W2232207765, https://openalex.org/W52840101, https://openalex.org/W2135105491, https://openalex.org/W2006772093, https://openalex.org/W2171094216, https://openalex.org/W2948130259, https://openalex.org/W2232417456, https://openalex.org/W2007940874, https://openalex.org/W1969779730, https://openalex.org/W2020958835, https://openalex.org/W2083290629, https://openalex.org/W2080947358, https://openalex.org/W2148417962, https://openalex.org/W2138865807, https://openalex.org/W1983607987, https://openalex.org/W2962991166, https://openalex.org/W1918349060 |
| referenced_works_count | 40 |
| abstract_inverted_index.a | 83, 99, 112 |
| abstract_inverted_index.1M | 160 |
| abstract_inverted_index.20 | 149 |
| abstract_inverted_index.30 | 165 |
| abstract_inverted_index.In | 93 |
| abstract_inverted_index.We | 110, 141 |
| abstract_inverted_index.an | 143 |
| abstract_inverted_index.as | 12, 57 |
| abstract_inverted_index.by | 117 |
| abstract_inverted_index.do | 63 |
| abstract_inverted_index.in | 5, 8, 78 |
| abstract_inverted_index.is | 47 |
| abstract_inverted_index.it | 155 |
| abstract_inverted_index.of | 34, 41, 53, 68, 115, 128, 146 |
| abstract_inverted_index.on | 66, 148 |
| abstract_inverted_index.or | 86 |
| abstract_inverted_index.to | 76, 159, 164 |
| abstract_inverted_index.up | 158, 163 |
| abstract_inverted_index.we | 96 |
| abstract_inverted_index.The | 37 |
| abstract_inverted_index.and | 7, 18, 23, 44, 70, 106, 152, 162 |
| abstract_inverted_index.are | 30, 73 |
| abstract_inverted_index.can | 156 |
| abstract_inverted_index.for | 21, 81, 101, 131 |
| abstract_inverted_index.may | 89 |
| abstract_inverted_index.not | 64 |
| abstract_inverted_index.the | 31, 79, 91, 125 |
| abstract_inverted_index.two | 126 |
| abstract_inverted_index.MVDs | 43, 107 |
| abstract_inverted_index.both | 42 |
| abstract_inverted_index.data | 40, 54 |
| abstract_inverted_index.from | 39, 108, 120, 138 |
| abstract_inverted_index.give | 111 |
| abstract_inverted_index.have | 2 |
| abstract_inverted_index.hold | 65 |
| abstract_inverted_index.more | 15, 48 |
| abstract_inverted_index.show | 153 |
| abstract_inverted_index.such | 11, 56 |
| abstract_inverted_index.than | 50 |
| abstract_inverted_index.that | 154 |
| abstract_inverted_index.then | 123, 134 |
| abstract_inverted_index.they | 72 |
| abstract_inverted_index.this | 94 |
| abstract_inverted_index.very | 74 |
| abstract_inverted_index.MVDs, | 133 |
| abstract_inverted_index.MVDs. | 140 |
| abstract_inverted_index.data, | 69 |
| abstract_inverted_index.data. | 109 |
| abstract_inverted_index.data; | 80 |
| abstract_inverted_index.forms | 52 |
| abstract_inverted_index.noise | 77 |
| abstract_inverted_index.other | 51 |
| abstract_inverted_index.paper | 95 |
| abstract_inverted_index.rows, | 161 |
| abstract_inverted_index.scale | 157 |
| abstract_inverted_index.these | 61 |
| abstract_inverted_index.tuple | 88 |
| abstract_inverted_index.using | 118 |
| abstract_inverted_index.wrong | 85 |
| abstract_inverted_index.(MVDs) | 29 |
| abstract_inverted_index.Maimon | 147 |
| abstract_inverted_index.blocks | 33 |
| abstract_inverted_index.mining | 130 |
| abstract_inverted_index.single | 84 |
| abstract_inverted_index.system | 100 |
| abstract_inverted_index.Acyclic | 0 |
| abstract_inverted_index.Maimon, | 98 |
| abstract_inverted_index.Maimon: | 129 |
| abstract_inverted_index.acyclic | 35, 45, 104, 136 |
| abstract_inverted_index.because | 60, 71 |
| abstract_inverted_index.conduct | 142 |
| abstract_inverted_index.design, | 14 |
| abstract_inverted_index.example | 82 |
| abstract_inverted_index.machine | 9, 24 |
| abstract_inverted_index.missing | 87 |
| abstract_inverted_index.notions | 119 |
| abstract_inverted_index.present | 97 |
| abstract_inverted_index.queries | 22 |
| abstract_inverted_index.schema. | 92 |
| abstract_inverted_index.schemes | 1, 46, 105, 137 |
| abstract_inverted_index.subsets | 67 |
| abstract_inverted_index.theory, | 122 |
| abstract_inverted_index.building | 32 |
| abstract_inverted_index.columns. | 166 |
| abstract_inverted_index.describe | 124 |
| abstract_inverted_index.improved | 13 |
| abstract_inverted_index.learning | 25 |
| abstract_inverted_index.numerous | 3 |
| abstract_inverted_index.schemes. | 36 |
| abstract_inverted_index.storage, | 17 |
| abstract_inverted_index.databases | 6 |
| abstract_inverted_index.datasets, | 151 |
| abstract_inverted_index.discovery | 38 |
| abstract_inverted_index.efficient | 16 |
| abstract_inverted_index.increased | 19 |
| abstract_inverted_index.learning, | 10 |
| abstract_inverted_index.sensitive | 75 |
| abstract_inverted_index.Functional | 58 |
| abstract_inverted_index.components | 127 |
| abstract_inverted_index.definition | 114 |
| abstract_inverted_index.evaluation | 145 |
| abstract_inverted_index.invalidate | 90 |
| abstract_inverted_index.principled | 113 |
| abstract_inverted_index.real-world | 150 |
| abstract_inverted_index.Multivalued | 27 |
| abstract_inverted_index.algorithms. | 26 |
| abstract_inverted_index.approximate | 103, 132, 139 |
| abstract_inverted_index.challenging | 49 |
| abstract_inverted_index.discovering | 102 |
| abstract_inverted_index.information | 121 |
| abstract_inverted_index.performance | 20 |
| abstract_inverted_index.applications | 4 |
| abstract_inverted_index.dependencies | 28, 62 |
| abstract_inverted_index.experimental | 144 |
| abstract_inverted_index.Dependencies, | 59 |
| abstract_inverted_index.dependencies, | 55 |
| abstract_inverted_index.approximation, | 116 |
| abstract_inverted_index.reconstructing | 135 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile |