Optimal Target-Oriented Knowledge Transportation For Aspect-Based Multimodal Sentiment Analysis. Article Swipe
Linhao Zhang
,
Jin Li
,
Guangluan Xu
,
Xiaoyu Li
,
Xian Sun
,
Zequn Zhang
,
Yanan Zhang
,
Qi Li
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.9781/ijimai.2024.02.005
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.9781/ijimai.2024.02.005
Aspect-based multimodal sentiment analysis under social media scenario aims to identify the sentiment polarities of each aspect term, which are mentioned in a piece of multimodal user-generated content. Previous approaches for this interdisciplinary multimodal task mainly rely on coarse-grained fusion mechanisms from the data-level or decision-level, which have the following three shortcomings:(1) ignoring the category knowledge of the sentiment target mentioned in the text) in visual information. (2) unable to assess the importance of maintaining target interaction during the unimodal encoding process, which results in indiscriminative representations considering various aspect terms. (3) suffering from the semantic gap between multiple modalities. To tackle the above challenging issues, we propose an optimal target-oriented knowledge transportation network (OtarNet) for this task. Firstly, the visual category knowledge is explicitly transported through input space translation and reformulation. Secondly, with the reformulated knowledge containing the target and category information, the target sensitivity is well maintained in the unimodal representations through a multistage target-oriented interaction mechanism. Finally, to eliminate the distributional modality gap by integrating complementary knowledge, the target-sensitive features of multiple modalities are implicitly transported based on the optimal transport interaction module. Our model achieves state-of-theart performance on three benchmark datasets: Twitter-15, Twitter-17 and Yelp, together with the extensive ablation study demonstrating the superiority and effectiveness of OtarNet.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.9781/ijimai.2024.02.005
- OA Status
- diamond
- Cited By
- 1
- References
- 49
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391988523
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4391988523Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.9781/ijimai.2024.02.005Digital Object Identifier
- Title
-
Optimal Target-Oriented Knowledge Transportation For Aspect-Based Multimodal Sentiment Analysis.Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-19Full publication date if available
- Authors
-
Linhao Zhang, Jin Li, Guangluan Xu, Xiaoyu Li, Xian Sun, Zequn Zhang, Yanan Zhang, Qi LiList of authors in order
- Landing page
-
https://doi.org/10.9781/ijimai.2024.02.005Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.9781/ijimai.2024.02.005Direct OA link when available
- Concepts
-
Computer science, Sentiment analysis, Data science, Artificial intelligence, Human–computer interactionTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- References (count)
-
49Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4391988523 |
|---|---|
| doi | https://doi.org/10.9781/ijimai.2024.02.005 |
| ids.doi | https://doi.org/10.9781/ijimai.2024.02.005 |
| ids.openalex | https://openalex.org/W4391988523 |
| fwci | 0.63877855 |
| type | article |
| title | Optimal Target-Oriented Knowledge Transportation For Aspect-Based Multimodal Sentiment Analysis. |
| biblio.issue | 4 |
| biblio.volume | 9 |
| biblio.last_page | 69 |
| biblio.first_page | 59 |
| topics[0].id | https://openalex.org/T13083 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9708999991416931 |
| 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 | Advanced Text Analysis Techniques |
| topics[1].id | https://openalex.org/T10664 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9690999984741211 |
| 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 | Sentiment Analysis and Opinion Mining |
| topics[2].id | https://openalex.org/T12016 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.907800018787384 |
| 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 | Web Data Mining and Analysis |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.8926935195922852 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C66402592 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5920864939689636 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q2271421 |
| concepts[1].display_name | Sentiment analysis |
| concepts[2].id | https://openalex.org/C2522767166 |
| concepts[2].level | 1 |
| concepts[2].score | 0.5190056562423706 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q2374463 |
| concepts[2].display_name | Data science |
| concepts[3].id | https://openalex.org/C154945302 |
| concepts[3].level | 1 |
| concepts[3].score | 0.42000824213027954 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[3].display_name | Artificial intelligence |
| concepts[4].id | https://openalex.org/C107457646 |
| concepts[4].level | 1 |
| concepts[4].score | 0.3527370095252991 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q207434 |
| concepts[4].display_name | Human–computer interaction |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.8926935195922852 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/sentiment-analysis |
| keywords[1].score | 0.5920864939689636 |
| keywords[1].display_name | Sentiment analysis |
| keywords[2].id | https://openalex.org/keywords/data-science |
| keywords[2].score | 0.5190056562423706 |
| keywords[2].display_name | Data science |
| keywords[3].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[3].score | 0.42000824213027954 |
| keywords[3].display_name | Artificial intelligence |
| keywords[4].id | https://openalex.org/keywords/human–computer-interaction |
| keywords[4].score | 0.3527370095252991 |
| keywords[4].display_name | Human–computer interaction |
| language | en |
| locations[0].id | doi:10.9781/ijimai.2024.02.005 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2738898797 |
| locations[0].source.issn | 1989-1660 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1989-1660 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | International Journal of Interactive Multimedia and Artificial Intelligence |
| locations[0].source.host_organization | https://openalex.org/P4310321767 |
| locations[0].source.host_organization_name | International University of La Rioja |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310321767 |
| locations[0].source.host_organization_lineage_names | International University of La Rioja |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | International Journal of Interactive Multimedia and Artificial Intelligence |
| locations[0].landing_page_url | https://doi.org/10.9781/ijimai.2024.02.005 |
| locations[1].id | pmh:oai:reunir.unir.net:123456789/16226 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400329 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | Re-Unir (International University of La Rioja) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | other-oa |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | https://openalex.org/licenses/other-oa |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://reunir.unir.net/handle/123456789/16226 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5014957302 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-8484-1733 |
| authorships[0].author.display_name | Linhao Zhang |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210137199 |
| authorships[0].affiliations[0].raw_affiliation_string | Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing (China) |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I4210165038 |
| authorships[0].affiliations[1].raw_affiliation_string | University of Chinese Academy of Sciences, Beijing (China) |
| authorships[0].affiliations[2].institution_ids | https://openalex.org/I4210165038 |
| authorships[0].affiliations[2].raw_affiliation_string | School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing (China) |
| authorships[0].institutions[0].id | https://openalex.org/I4210137199 |
| authorships[0].institutions[0].ror | https://ror.org/0419fj215 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I19820366, https://openalex.org/I4210137199 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Aerospace Information Research Institute |
| authorships[0].institutions[1].id | https://openalex.org/I19820366 |
| authorships[0].institutions[1].ror | https://ror.org/034t30j35 |
| authorships[0].institutions[1].type | government |
| authorships[0].institutions[1].lineage | https://openalex.org/I19820366 |
| authorships[0].institutions[1].country_code | CN |
| authorships[0].institutions[1].display_name | Chinese Academy of Sciences |
| authorships[0].institutions[2].id | https://openalex.org/I4210165038 |
| authorships[0].institutions[2].ror | https://ror.org/05qbk4x57 |
| authorships[0].institutions[2].type | education |
| authorships[0].institutions[2].lineage | https://openalex.org/I19820366, https://openalex.org/I4210165038 |
| authorships[0].institutions[2].country_code | CN |
| authorships[0].institutions[2].display_name | University of Chinese Academy of Sciences |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Linhao Zhang |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing (China), School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing (China), University of Chinese Academy of Sciences, Beijing (China) |
| authorships[1].author.id | https://openalex.org/A5100781249 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-0260-3169 |
| authorships[1].author.display_name | Jin Li |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Li Jin |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5057853630 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-3529-593X |
| authorships[2].author.display_name | Guangluan Xu |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210137199 |
| authorships[2].affiliations[0].raw_affiliation_string | Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing (China) |
| authorships[2].institutions[0].id | https://openalex.org/I4210137199 |
| authorships[2].institutions[0].ror | https://ror.org/0419fj215 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I19820366, https://openalex.org/I4210137199 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | Aerospace Information Research Institute |
| authorships[2].institutions[1].id | https://openalex.org/I19820366 |
| authorships[2].institutions[1].ror | https://ror.org/034t30j35 |
| authorships[2].institutions[1].type | government |
| authorships[2].institutions[1].lineage | https://openalex.org/I19820366 |
| authorships[2].institutions[1].country_code | CN |
| authorships[2].institutions[1].display_name | Chinese Academy of Sciences |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Guangluan Xu |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing (China) |
| authorships[3].author.id | https://openalex.org/A5100449169 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-0286-6660 |
| authorships[3].author.display_name | Xiaoyu Li |
| authorships[3].countries | CN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210137199 |
| authorships[3].affiliations[0].raw_affiliation_string | Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing (China) |
| authorships[3].institutions[0].id | https://openalex.org/I4210137199 |
| authorships[3].institutions[0].ror | https://ror.org/0419fj215 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I19820366, https://openalex.org/I4210137199 |
| authorships[3].institutions[0].country_code | CN |
| authorships[3].institutions[0].display_name | Aerospace Information Research Institute |
| authorships[3].institutions[1].id | https://openalex.org/I19820366 |
| authorships[3].institutions[1].ror | https://ror.org/034t30j35 |
| authorships[3].institutions[1].type | government |
| authorships[3].institutions[1].lineage | https://openalex.org/I19820366 |
| authorships[3].institutions[1].country_code | CN |
| authorships[3].institutions[1].display_name | Chinese Academy of Sciences |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Xiaoyu Li |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing (China) |
| authorships[4].author.id | https://openalex.org/A5100835884 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | Xian Sun |
| authorships[4].countries | CN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210137199 |
| authorships[4].affiliations[0].raw_affiliation_string | Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing (China) |
| authorships[4].institutions[0].id | https://openalex.org/I4210137199 |
| authorships[4].institutions[0].ror | https://ror.org/0419fj215 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I19820366, https://openalex.org/I4210137199 |
| authorships[4].institutions[0].country_code | CN |
| authorships[4].institutions[0].display_name | Aerospace Information Research Institute |
| authorships[4].institutions[1].id | https://openalex.org/I19820366 |
| authorships[4].institutions[1].ror | https://ror.org/034t30j35 |
| authorships[4].institutions[1].type | government |
| authorships[4].institutions[1].lineage | https://openalex.org/I19820366 |
| authorships[4].institutions[1].country_code | CN |
| authorships[4].institutions[1].display_name | Chinese Academy of Sciences |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Xian Sun |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing (China) |
| authorships[5].author.id | https://openalex.org/A5101810352 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-2138-845X |
| authorships[5].author.display_name | Zequn Zhang |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Zequn Zhang |
| authorships[5].is_corresponding | False |
| authorships[6].author.id | https://openalex.org/A5005273282 |
| authorships[6].author.orcid | https://orcid.org/0009-0006-7278-0378 |
| authorships[6].author.display_name | Yanan Zhang |
| authorships[6].countries | CN |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I24185976 |
| authorships[6].affiliations[0].raw_affiliation_string | Sichuan University, Chengdu (China) |
| authorships[6].affiliations[1].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210137199 |
| authorships[6].affiliations[1].raw_affiliation_string | Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing (China) |
| authorships[6].institutions[0].id | https://openalex.org/I4210137199 |
| authorships[6].institutions[0].ror | https://ror.org/0419fj215 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I19820366, https://openalex.org/I4210137199 |
| authorships[6].institutions[0].country_code | CN |
| authorships[6].institutions[0].display_name | Aerospace Information Research Institute |
| authorships[6].institutions[1].id | https://openalex.org/I19820366 |
| authorships[6].institutions[1].ror | https://ror.org/034t30j35 |
| authorships[6].institutions[1].type | government |
| authorships[6].institutions[1].lineage | https://openalex.org/I19820366 |
| authorships[6].institutions[1].country_code | CN |
| authorships[6].institutions[1].display_name | Chinese Academy of Sciences |
| authorships[6].institutions[2].id | https://openalex.org/I24185976 |
| authorships[6].institutions[2].ror | https://ror.org/011ashp19 |
| authorships[6].institutions[2].type | education |
| authorships[6].institutions[2].lineage | https://openalex.org/I24185976 |
| authorships[6].institutions[2].country_code | CN |
| authorships[6].institutions[2].display_name | Sichuan University |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Yanan Zhang |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing (China), Sichuan University, Chengdu (China) |
| authorships[7].author.id | https://openalex.org/A5100350178 |
| authorships[7].author.orcid | https://orcid.org/0000-0002-0033-6204 |
| authorships[7].author.display_name | Qi Li |
| authorships[7].countries | CN |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I25254941 |
| authorships[7].affiliations[0].raw_affiliation_string | Faculty of Psychology, Beijing Normal University, Beijing (China) |
| authorships[7].affiliations[1].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210137199 |
| authorships[7].affiliations[1].raw_affiliation_string | Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing (China) |
| authorships[7].institutions[0].id | https://openalex.org/I4210137199 |
| authorships[7].institutions[0].ror | https://ror.org/0419fj215 |
| authorships[7].institutions[0].type | education |
| authorships[7].institutions[0].lineage | https://openalex.org/I19820366, https://openalex.org/I4210137199 |
| authorships[7].institutions[0].country_code | CN |
| authorships[7].institutions[0].display_name | Aerospace Information Research Institute |
| authorships[7].institutions[1].id | https://openalex.org/I25254941 |
| authorships[7].institutions[1].ror | https://ror.org/022k4wk35 |
| authorships[7].institutions[1].type | education |
| authorships[7].institutions[1].lineage | https://openalex.org/I25254941 |
| authorships[7].institutions[1].country_code | CN |
| authorships[7].institutions[1].display_name | Beijing Normal University |
| authorships[7].institutions[2].id | https://openalex.org/I19820366 |
| authorships[7].institutions[2].ror | https://ror.org/034t30j35 |
| authorships[7].institutions[2].type | government |
| authorships[7].institutions[2].lineage | https://openalex.org/I19820366 |
| authorships[7].institutions[2].country_code | CN |
| authorships[7].institutions[2].display_name | Chinese Academy of Sciences |
| authorships[7].author_position | last |
| authorships[7].raw_author_name | Qi Li |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing (China), Faculty of Psychology, Beijing Normal University, Beijing (China) |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.9781/ijimai.2024.02.005 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Optimal Target-Oriented Knowledge Transportation For Aspect-Based Multimodal Sentiment Analysis. |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T13083 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9708999991416931 |
| 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 | Advanced Text Analysis Techniques |
| related_works | https://openalex.org/W2748952813, https://openalex.org/W3089396779, https://openalex.org/W2548633793, https://openalex.org/W3013279174, https://openalex.org/W2941935829, https://openalex.org/W2596247554, https://openalex.org/W4301373556, https://openalex.org/W3132372214, https://openalex.org/W4224284088, https://openalex.org/W2243502667 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 2 |
| best_oa_location.id | doi:10.9781/ijimai.2024.02.005 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2738898797 |
| best_oa_location.source.issn | 1989-1660 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1989-1660 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | International Journal of Interactive Multimedia and Artificial Intelligence |
| best_oa_location.source.host_organization | https://openalex.org/P4310321767 |
| best_oa_location.source.host_organization_name | International University of La Rioja |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310321767 |
| best_oa_location.source.host_organization_lineage_names | International University of La Rioja |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | International Journal of Interactive Multimedia and Artificial Intelligence |
| best_oa_location.landing_page_url | https://doi.org/10.9781/ijimai.2024.02.005 |
| primary_location.id | doi:10.9781/ijimai.2024.02.005 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2738898797 |
| primary_location.source.issn | 1989-1660 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1989-1660 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | International Journal of Interactive Multimedia and Artificial Intelligence |
| primary_location.source.host_organization | https://openalex.org/P4310321767 |
| primary_location.source.host_organization_name | International University of La Rioja |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310321767 |
| primary_location.source.host_organization_lineage_names | International University of La Rioja |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | International Journal of Interactive Multimedia and Artificial Intelligence |
| primary_location.landing_page_url | https://doi.org/10.9781/ijimai.2024.02.005 |
| publication_date | 2024-02-19 |
| publication_year | 2024 |
| referenced_works | https://openalex.org/W3213870678, https://openalex.org/W3175212568, https://openalex.org/W2910191085, https://openalex.org/W3167308647, https://openalex.org/W2767249564, https://openalex.org/W2985056549, https://openalex.org/W2923978210, https://openalex.org/W1976692960, https://openalex.org/W2952357537, https://openalex.org/W3095024162, https://openalex.org/W3205872166, https://openalex.org/W2798298921, https://openalex.org/W3041730883, https://openalex.org/W2963168371, https://openalex.org/W2891778157, https://openalex.org/W3119160044, https://openalex.org/W4302571896, https://openalex.org/W2962717755, https://openalex.org/W3096609285, https://openalex.org/W2971586182, https://openalex.org/W2966765144, https://openalex.org/W3018312910, https://openalex.org/W2951278869, https://openalex.org/W4287753648, https://openalex.org/W2600278912, https://openalex.org/W2061116763, https://openalex.org/W2757541972, https://openalex.org/W3187172219, https://openalex.org/W2098689807, https://openalex.org/W4283802945, https://openalex.org/W4213422824, https://openalex.org/W2964260444, https://openalex.org/W2075456404, https://openalex.org/W2905551935, https://openalex.org/W2113125055, https://openalex.org/W2955260208, https://openalex.org/W2165855670, https://openalex.org/W2462831000, https://openalex.org/W2963702064, https://openalex.org/W2562607067, https://openalex.org/W2194775991, https://openalex.org/W3212125355, https://openalex.org/W2472490454, https://openalex.org/W2788647998, https://openalex.org/W2187168313, https://openalex.org/W2896457183, https://openalex.org/W2789190634, https://openalex.org/W2963710346, https://openalex.org/W3037865115 |
| referenced_works_count | 49 |
| abstract_inverted_index.a | 22, 154 |
| abstract_inverted_index.To | 100 |
| abstract_inverted_index.an | 108 |
| abstract_inverted_index.by | 166 |
| abstract_inverted_index.in | 21, 61, 64, 84, 149 |
| abstract_inverted_index.is | 123, 146 |
| abstract_inverted_index.of | 14, 24, 56, 73, 173, 210 |
| abstract_inverted_index.on | 37, 180, 191 |
| abstract_inverted_index.or | 44 |
| abstract_inverted_index.to | 9, 69, 160 |
| abstract_inverted_index.we | 106 |
| abstract_inverted_index.(2) | 67 |
| abstract_inverted_index.(3) | 91 |
| abstract_inverted_index.Our | 186 |
| abstract_inverted_index.and | 130, 140, 197, 208 |
| abstract_inverted_index.are | 19, 176 |
| abstract_inverted_index.for | 30, 115 |
| abstract_inverted_index.gap | 96, 165 |
| abstract_inverted_index.the | 11, 42, 48, 53, 57, 62, 71, 78, 94, 102, 119, 134, 138, 143, 150, 162, 170, 181, 201, 206 |
| abstract_inverted_index.aims | 8 |
| abstract_inverted_index.each | 15 |
| abstract_inverted_index.from | 41, 93 |
| abstract_inverted_index.have | 47 |
| abstract_inverted_index.rely | 36 |
| abstract_inverted_index.task | 34 |
| abstract_inverted_index.this | 31, 116 |
| abstract_inverted_index.well | 147 |
| abstract_inverted_index.with | 133, 200 |
| abstract_inverted_index.Yelp, | 198 |
| abstract_inverted_index.above | 103 |
| abstract_inverted_index.based | 179 |
| abstract_inverted_index.input | 127 |
| abstract_inverted_index.media | 6 |
| abstract_inverted_index.model | 187 |
| abstract_inverted_index.piece | 23 |
| abstract_inverted_index.space | 128 |
| abstract_inverted_index.study | 204 |
| abstract_inverted_index.task. | 117 |
| abstract_inverted_index.term, | 17 |
| abstract_inverted_index.text) | 63 |
| abstract_inverted_index.three | 50, 192 |
| abstract_inverted_index.under | 4 |
| abstract_inverted_index.which | 18, 46, 82 |
| abstract_inverted_index.aspect | 16, 89 |
| abstract_inverted_index.assess | 70 |
| abstract_inverted_index.during | 77 |
| abstract_inverted_index.fusion | 39 |
| abstract_inverted_index.mainly | 35 |
| abstract_inverted_index.social | 5 |
| abstract_inverted_index.tackle | 101 |
| abstract_inverted_index.target | 59, 75, 139, 144 |
| abstract_inverted_index.terms. | 90 |
| abstract_inverted_index.unable | 68 |
| abstract_inverted_index.visual | 65, 120 |
| abstract_inverted_index.between | 97 |
| abstract_inverted_index.issues, | 105 |
| abstract_inverted_index.module. | 185 |
| abstract_inverted_index.network | 113 |
| abstract_inverted_index.optimal | 109, 182 |
| abstract_inverted_index.propose | 107 |
| abstract_inverted_index.results | 83 |
| abstract_inverted_index.through | 126, 153 |
| abstract_inverted_index.various | 88 |
| abstract_inverted_index.Finally, | 159 |
| abstract_inverted_index.Firstly, | 118 |
| abstract_inverted_index.OtarNet. | 211 |
| abstract_inverted_index.Previous | 28 |
| abstract_inverted_index.ablation | 203 |
| abstract_inverted_index.achieves | 188 |
| abstract_inverted_index.analysis | 3 |
| abstract_inverted_index.category | 54, 121, 141 |
| abstract_inverted_index.content. | 27 |
| abstract_inverted_index.encoding | 80 |
| abstract_inverted_index.features | 172 |
| abstract_inverted_index.identify | 10 |
| abstract_inverted_index.ignoring | 52 |
| abstract_inverted_index.modality | 164 |
| abstract_inverted_index.multiple | 98, 174 |
| abstract_inverted_index.process, | 81 |
| abstract_inverted_index.scenario | 7 |
| abstract_inverted_index.semantic | 95 |
| abstract_inverted_index.together | 199 |
| abstract_inverted_index.unimodal | 79, 151 |
| abstract_inverted_index.(OtarNet) | 114 |
| abstract_inverted_index.Secondly, | 132 |
| abstract_inverted_index.benchmark | 193 |
| abstract_inverted_index.datasets: | 194 |
| abstract_inverted_index.eliminate | 161 |
| abstract_inverted_index.extensive | 202 |
| abstract_inverted_index.following | 49 |
| abstract_inverted_index.knowledge | 55, 111, 122, 136 |
| abstract_inverted_index.mentioned | 20, 60 |
| abstract_inverted_index.sentiment | 2, 12, 58 |
| abstract_inverted_index.suffering | 92 |
| abstract_inverted_index.transport | 183 |
| abstract_inverted_index.Twitter-17 | 196 |
| abstract_inverted_index.approaches | 29 |
| abstract_inverted_index.containing | 137 |
| abstract_inverted_index.data-level | 43 |
| abstract_inverted_index.explicitly | 124 |
| abstract_inverted_index.implicitly | 177 |
| abstract_inverted_index.importance | 72 |
| abstract_inverted_index.knowledge, | 169 |
| abstract_inverted_index.maintained | 148 |
| abstract_inverted_index.mechanism. | 158 |
| abstract_inverted_index.mechanisms | 40 |
| abstract_inverted_index.modalities | 175 |
| abstract_inverted_index.multimodal | 1, 25, 33 |
| abstract_inverted_index.multistage | 155 |
| abstract_inverted_index.polarities | 13 |
| abstract_inverted_index.Twitter-15, | 195 |
| abstract_inverted_index.challenging | 104 |
| abstract_inverted_index.considering | 87 |
| abstract_inverted_index.integrating | 167 |
| abstract_inverted_index.interaction | 76, 157, 184 |
| abstract_inverted_index.maintaining | 74 |
| abstract_inverted_index.modalities. | 99 |
| abstract_inverted_index.performance | 190 |
| abstract_inverted_index.sensitivity | 145 |
| abstract_inverted_index.superiority | 207 |
| abstract_inverted_index.translation | 129 |
| abstract_inverted_index.transported | 125, 178 |
| abstract_inverted_index.Aspect-based | 0 |
| abstract_inverted_index.information, | 142 |
| abstract_inverted_index.information. | 66 |
| abstract_inverted_index.reformulated | 135 |
| abstract_inverted_index.complementary | 168 |
| abstract_inverted_index.demonstrating | 205 |
| abstract_inverted_index.effectiveness | 209 |
| abstract_inverted_index.coarse-grained | 38 |
| abstract_inverted_index.distributional | 163 |
| abstract_inverted_index.reformulation. | 131 |
| abstract_inverted_index.transportation | 112 |
| abstract_inverted_index.user-generated | 26 |
| abstract_inverted_index.decision-level, | 45 |
| abstract_inverted_index.representations | 86, 152 |
| abstract_inverted_index.state-of-theart | 189 |
| abstract_inverted_index.target-oriented | 110, 156 |
| abstract_inverted_index.indiscriminative | 85 |
| abstract_inverted_index.shortcomings:(1) | 51 |
| abstract_inverted_index.target-sensitive | 171 |
| abstract_inverted_index.interdisciplinary | 32 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile.value | 0.64852916 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |