What and Where: A Context-based Recommendation System for Object Insertion Article Swipe
Song–Hai Zhang
,
Zhengping Zhou
,
Bin Liu
,
Xin Dong
,
Dun Liang
,
Peter Hall
,
Shi‐Min Hu
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1811.09783
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1811.09783
In this work, we propose a novel topic consisting of two dual tasks: 1) given a scene, recommend objects to insert, 2) given an object category, retrieve suitable background scenes. A bounding box for the inserted object is predicted in both tasks, which helps downstream applications such as semi-automated advertising and video composition. The major challenge lies in the fact that the target object is neither present nor localized at test time, whereas available datasets only provide scenes with existing objects. To tackle this problem, we build an unsupervised algorithm based on object-level contexts, which explicitly models the joint probability distribution of object categories and bounding boxes with a Gaussian mixture model. Experiments on our newly annotated test set demonstrate that our system outperforms existing baselines on all subtasks, and do so under a unified framework. Our contribution promises future extensions and applications.
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1811.09783
- https://arxiv.org/pdf/1811.09783
- OA Status
- green
- Cited By
- 3
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2901904725
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2901904725Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.1811.09783Digital Object Identifier
- Title
-
What and Where: A Context-based Recommendation System for Object InsertionWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-11-24Full publication date if available
- Authors
-
Song–Hai Zhang, Zhengping Zhou, Bin Liu, Xin Dong, Dun Liang, Peter Hall, Shi‐Min HuList of authors in order
- Landing page
-
https://arxiv.org/abs/1811.09783Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1811.09783Direct 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/1811.09783Direct OA link when available
- Concepts
-
Computer science, Bounding overwatch, Object (grammar), Minimum bounding box, Context (archaeology), Set (abstract data type), Artificial intelligence, Mixture model, Dual (grammatical number), Gaussian, Image (mathematics), Programming language, Art, Physics, Paleontology, Quantum mechanics, Biology, LiteratureTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 2Per-year citation counts (last 5 years)
- References (count)
-
23Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2901904725 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.1811.09783 |
| ids.doi | https://doi.org/10.48550/arxiv.1811.09783 |
| ids.mag | 2901904725 |
| ids.openalex | https://openalex.org/W2901904725 |
| fwci | |
| type | preprint |
| title | What and Where: A Context-based Recommendation System for Object Insertion |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T11714 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9998999834060669 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1707 |
| topics[0].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[0].display_name | Multimodal Machine Learning Applications |
| topics[1].id | https://openalex.org/T10627 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9998000264167786 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1707 |
| topics[1].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[1].display_name | Advanced Image and Video Retrieval Techniques |
| topics[2].id | https://openalex.org/T10036 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9991999864578247 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1707 |
| topics[2].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[2].display_name | Advanced Neural Network Applications |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.8136099576950073 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C63584917 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7747586965560913 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q333286 |
| concepts[1].display_name | Bounding overwatch |
| concepts[2].id | https://openalex.org/C2781238097 |
| concepts[2].level | 2 |
| concepts[2].score | 0.7568343877792358 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q175026 |
| concepts[2].display_name | Object (grammar) |
| concepts[3].id | https://openalex.org/C147037132 |
| concepts[3].level | 3 |
| concepts[3].score | 0.7516446113586426 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q6865426 |
| concepts[3].display_name | Minimum bounding box |
| concepts[4].id | https://openalex.org/C2779343474 |
| concepts[4].level | 2 |
| concepts[4].score | 0.6025095582008362 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q3109175 |
| concepts[4].display_name | Context (archaeology) |
| concepts[5].id | https://openalex.org/C177264268 |
| concepts[5].level | 2 |
| concepts[5].score | 0.6019114851951599 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q1514741 |
| concepts[5].display_name | Set (abstract data type) |
| concepts[6].id | https://openalex.org/C154945302 |
| concepts[6].level | 1 |
| concepts[6].score | 0.5138735771179199 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[6].display_name | Artificial intelligence |
| concepts[7].id | https://openalex.org/C61224824 |
| concepts[7].level | 2 |
| concepts[7].score | 0.47877562046051025 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q2260434 |
| concepts[7].display_name | Mixture model |
| concepts[8].id | https://openalex.org/C2780980858 |
| concepts[8].level | 2 |
| concepts[8].score | 0.4392697513103485 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q110022 |
| concepts[8].display_name | Dual (grammatical number) |
| concepts[9].id | https://openalex.org/C163716315 |
| concepts[9].level | 2 |
| concepts[9].score | 0.4124397933483124 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q901177 |
| concepts[9].display_name | Gaussian |
| concepts[10].id | https://openalex.org/C115961682 |
| concepts[10].level | 2 |
| concepts[10].score | 0.27854782342910767 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q860623 |
| concepts[10].display_name | Image (mathematics) |
| concepts[11].id | https://openalex.org/C199360897 |
| concepts[11].level | 1 |
| concepts[11].score | 0.08316552639007568 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[11].display_name | Programming language |
| concepts[12].id | https://openalex.org/C142362112 |
| concepts[12].level | 0 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q735 |
| concepts[12].display_name | Art |
| concepts[13].id | https://openalex.org/C121332964 |
| concepts[13].level | 0 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[13].display_name | Physics |
| concepts[14].id | https://openalex.org/C151730666 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q7205 |
| concepts[14].display_name | Paleontology |
| concepts[15].id | https://openalex.org/C62520636 |
| concepts[15].level | 1 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q944 |
| concepts[15].display_name | Quantum mechanics |
| concepts[16].id | https://openalex.org/C86803240 |
| concepts[16].level | 0 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[16].display_name | Biology |
| concepts[17].id | https://openalex.org/C124952713 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q8242 |
| concepts[17].display_name | Literature |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.8136099576950073 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/bounding-overwatch |
| keywords[1].score | 0.7747586965560913 |
| keywords[1].display_name | Bounding overwatch |
| keywords[2].id | https://openalex.org/keywords/object |
| keywords[2].score | 0.7568343877792358 |
| keywords[2].display_name | Object (grammar) |
| keywords[3].id | https://openalex.org/keywords/minimum-bounding-box |
| keywords[3].score | 0.7516446113586426 |
| keywords[3].display_name | Minimum bounding box |
| keywords[4].id | https://openalex.org/keywords/context |
| keywords[4].score | 0.6025095582008362 |
| keywords[4].display_name | Context (archaeology) |
| keywords[5].id | https://openalex.org/keywords/set |
| keywords[5].score | 0.6019114851951599 |
| keywords[5].display_name | Set (abstract data type) |
| keywords[6].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[6].score | 0.5138735771179199 |
| keywords[6].display_name | Artificial intelligence |
| keywords[7].id | https://openalex.org/keywords/mixture-model |
| keywords[7].score | 0.47877562046051025 |
| keywords[7].display_name | Mixture model |
| keywords[8].id | https://openalex.org/keywords/dual |
| keywords[8].score | 0.4392697513103485 |
| keywords[8].display_name | Dual (grammatical number) |
| keywords[9].id | https://openalex.org/keywords/gaussian |
| keywords[9].score | 0.4124397933483124 |
| keywords[9].display_name | Gaussian |
| keywords[10].id | https://openalex.org/keywords/image |
| keywords[10].score | 0.27854782342910767 |
| keywords[10].display_name | Image (mathematics) |
| keywords[11].id | https://openalex.org/keywords/programming-language |
| keywords[11].score | 0.08316552639007568 |
| keywords[11].display_name | Programming language |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:1811.09783 |
| 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/1811.09783 |
| 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/1811.09783 |
| locations[1].id | doi:10.48550/arxiv.1811.09783 |
| 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.1811.09783 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5049883689 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-0460-1586 |
| authorships[0].author.display_name | Song–Hai Zhang |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Song-Hai Zhang |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5085639468 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-4706-5499 |
| authorships[1].author.display_name | Zhengping Zhou |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Zhengping Zhou |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5100395493 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-3977-8800 |
| authorships[2].author.display_name | Bin Liu |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Bin Liu |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5088720980 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-8727-8088 |
| authorships[3].author.display_name | Xin Dong |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Xin Dong |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5031273483 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | Dun Liang |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Dun Liang |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5102977753 |
| authorships[5].author.orcid | https://orcid.org/0009-0006-5699-5483 |
| authorships[5].author.display_name | Peter Hall |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Peter Hall |
| authorships[5].is_corresponding | False |
| authorships[6].author.id | https://openalex.org/A5037233582 |
| authorships[6].author.orcid | https://orcid.org/0000-0001-7507-6542 |
| authorships[6].author.display_name | Shi‐Min Hu |
| authorships[6].author_position | last |
| authorships[6].raw_author_name | Shi-Min Hu |
| authorships[6].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/1811.09783 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2018-11-29T00:00:00 |
| display_name | What and Where: A Context-based Recommendation System for Object Insertion |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T11714 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9998999834060669 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1707 |
| primary_topic.subfield.display_name | Computer Vision and Pattern Recognition |
| primary_topic.display_name | Multimodal Machine Learning Applications |
| related_works | https://openalex.org/W4237171675, https://openalex.org/W3036286480, https://openalex.org/W4287027631, https://openalex.org/W3192357901, https://openalex.org/W2387360586, https://openalex.org/W2952736415, https://openalex.org/W3209723314, https://openalex.org/W3205398323, https://openalex.org/W2883297582, https://openalex.org/W4390524233 |
| cited_by_count | 3 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 2 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:1811.09783 |
| 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/1811.09783 |
| 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/1811.09783 |
| primary_location.id | pmh:oai:arXiv.org:1811.09783 |
| 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/1811.09783 |
| 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/1811.09783 |
| publication_date | 2018-11-24 |
| publication_year | 2018 |
| referenced_works | https://openalex.org/W2499468060, https://openalex.org/W1690919088, https://openalex.org/W2950328304, https://openalex.org/W2656999302, https://openalex.org/W2949474740, https://openalex.org/W2953106684, https://openalex.org/W2286929393, https://openalex.org/W2069870183, https://openalex.org/W2102605133, https://openalex.org/W2951343884, https://openalex.org/W2622090382, https://openalex.org/W2077069816, https://openalex.org/W1971067901, https://openalex.org/W2784790939, https://openalex.org/W2081293863, https://openalex.org/W2101611867, https://openalex.org/W2737766105, https://openalex.org/W3106250896, https://openalex.org/W1861492603, https://openalex.org/W2194775991, https://openalex.org/W2395611524, https://openalex.org/W2097117768, https://openalex.org/W1817277359 |
| referenced_works_count | 23 |
| abstract_inverted_index.A | 30 |
| abstract_inverted_index.a | 5, 15, 108, 133 |
| abstract_inverted_index.1) | 13 |
| abstract_inverted_index.2) | 21 |
| abstract_inverted_index.In | 0 |
| abstract_inverted_index.To | 81 |
| abstract_inverted_index.an | 23, 87 |
| abstract_inverted_index.as | 47 |
| abstract_inverted_index.at | 69 |
| abstract_inverted_index.do | 130 |
| abstract_inverted_index.in | 39, 57 |
| abstract_inverted_index.is | 37, 64 |
| abstract_inverted_index.of | 9, 101 |
| abstract_inverted_index.on | 91, 113, 126 |
| abstract_inverted_index.so | 131 |
| abstract_inverted_index.to | 19 |
| abstract_inverted_index.we | 3, 85 |
| abstract_inverted_index.Our | 136 |
| abstract_inverted_index.The | 53 |
| abstract_inverted_index.all | 127 |
| abstract_inverted_index.and | 50, 104, 129, 141 |
| abstract_inverted_index.box | 32 |
| abstract_inverted_index.for | 33 |
| abstract_inverted_index.nor | 67 |
| abstract_inverted_index.our | 114, 121 |
| abstract_inverted_index.set | 118 |
| abstract_inverted_index.the | 34, 58, 61, 97 |
| abstract_inverted_index.two | 10 |
| abstract_inverted_index.both | 40 |
| abstract_inverted_index.dual | 11 |
| abstract_inverted_index.fact | 59 |
| abstract_inverted_index.lies | 56 |
| abstract_inverted_index.only | 75 |
| abstract_inverted_index.such | 46 |
| abstract_inverted_index.test | 70, 117 |
| abstract_inverted_index.that | 60, 120 |
| abstract_inverted_index.this | 1, 83 |
| abstract_inverted_index.with | 78, 107 |
| abstract_inverted_index.based | 90 |
| abstract_inverted_index.boxes | 106 |
| abstract_inverted_index.build | 86 |
| abstract_inverted_index.given | 14, 22 |
| abstract_inverted_index.helps | 43 |
| abstract_inverted_index.joint | 98 |
| abstract_inverted_index.major | 54 |
| abstract_inverted_index.newly | 115 |
| abstract_inverted_index.novel | 6 |
| abstract_inverted_index.time, | 71 |
| abstract_inverted_index.topic | 7 |
| abstract_inverted_index.under | 132 |
| abstract_inverted_index.video | 51 |
| abstract_inverted_index.which | 42, 94 |
| abstract_inverted_index.work, | 2 |
| abstract_inverted_index.future | 139 |
| abstract_inverted_index.model. | 111 |
| abstract_inverted_index.models | 96 |
| abstract_inverted_index.object | 24, 36, 63, 102 |
| abstract_inverted_index.scene, | 16 |
| abstract_inverted_index.scenes | 77 |
| abstract_inverted_index.system | 122 |
| abstract_inverted_index.tackle | 82 |
| abstract_inverted_index.target | 62 |
| abstract_inverted_index.tasks, | 41 |
| abstract_inverted_index.tasks: | 12 |
| abstract_inverted_index.insert, | 20 |
| abstract_inverted_index.mixture | 110 |
| abstract_inverted_index.neither | 65 |
| abstract_inverted_index.objects | 18 |
| abstract_inverted_index.present | 66 |
| abstract_inverted_index.propose | 4 |
| abstract_inverted_index.provide | 76 |
| abstract_inverted_index.scenes. | 29 |
| abstract_inverted_index.unified | 134 |
| abstract_inverted_index.whereas | 72 |
| abstract_inverted_index.Gaussian | 109 |
| abstract_inverted_index.bounding | 31, 105 |
| abstract_inverted_index.datasets | 74 |
| abstract_inverted_index.existing | 79, 124 |
| abstract_inverted_index.inserted | 35 |
| abstract_inverted_index.objects. | 80 |
| abstract_inverted_index.problem, | 84 |
| abstract_inverted_index.promises | 138 |
| abstract_inverted_index.retrieve | 26 |
| abstract_inverted_index.suitable | 27 |
| abstract_inverted_index.algorithm | 89 |
| abstract_inverted_index.annotated | 116 |
| abstract_inverted_index.available | 73 |
| abstract_inverted_index.baselines | 125 |
| abstract_inverted_index.category, | 25 |
| abstract_inverted_index.challenge | 55 |
| abstract_inverted_index.contexts, | 93 |
| abstract_inverted_index.localized | 68 |
| abstract_inverted_index.predicted | 38 |
| abstract_inverted_index.recommend | 17 |
| abstract_inverted_index.subtasks, | 128 |
| abstract_inverted_index.background | 28 |
| abstract_inverted_index.categories | 103 |
| abstract_inverted_index.consisting | 8 |
| abstract_inverted_index.downstream | 44 |
| abstract_inverted_index.explicitly | 95 |
| abstract_inverted_index.extensions | 140 |
| abstract_inverted_index.framework. | 135 |
| abstract_inverted_index.Experiments | 112 |
| abstract_inverted_index.advertising | 49 |
| abstract_inverted_index.demonstrate | 119 |
| abstract_inverted_index.outperforms | 123 |
| abstract_inverted_index.probability | 99 |
| abstract_inverted_index.applications | 45 |
| abstract_inverted_index.composition. | 52 |
| abstract_inverted_index.contribution | 137 |
| abstract_inverted_index.distribution | 100 |
| abstract_inverted_index.object-level | 92 |
| abstract_inverted_index.unsupervised | 88 |
| abstract_inverted_index.applications. | 142 |
| abstract_inverted_index.semi-automated | 48 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile |