{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/116119"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/116119","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Towards image-based node embedding: A novel approach for enriching multimodal representation","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01","abstract_has_math":false,"creators":["Seo, Seung Byum"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Applied Mathematics","degree_department":null,"school":null,"contributors":["Delgosha, Payam"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-08","date_published":"2022-08","updated_at":"2026-07-22T22:24:55Z","subjects":["multimodal learning","representation learning","graph neural network","natural language processing"],"languages":["en","eng"],"rights":["Copyright 2022 Seung Byum Seo"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/116119","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Delgosha, Payam"]},{"key":"dc:creator","label":"Author","values":["Seo, Seung Byum"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-08","2022-07-21"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Applied Mathematics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["multimodal learning","representation learning","graph neural network","natural language processing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2022 Seung Byum Seo"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/116119"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01","The student, Seung Byum Seo, accepted the attached license on 2022-07-19 at 01:16.","The student, Seung Byum Seo, submitted this Thesis for approval on 2022-07-20 at 00:13.","This Thesis was approved for publication on 2022-07-21 at 15:54.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18373 on 2022-11-15 at 21:40:35","While there have been advances in Natural Language Processing (NLP), their success is mainly gained by applying a self-attention mechanism into single or multi-modalities. While this approach has brought significant improvements in multiple downstream tasks, it fails to capture the interaction between different entities. Therefore, we propose MM-GATBT, a multimodal graph representation learning model that captures not only the relational semantics within one modality but also the interactions between different modalities. Specifically, the proposed method constructs image-based node embedding which contains relational semantics of entities. Our empirical results show that MM-GATBT achieves state-of-the-art results among all published papers on the MM-IMDb dataset."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Towards image-based node embedding: A novel approach for enriching multimodal representation"]}]}],"canonical_facts":{"dc:contributor":["Delgosha, Payam"],"dc:creator":["Seo, Seung Byum"],"dc:date":["2022-08","2022-07-21"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01","The student, Seung Byum Seo, accepted the attached license on 2022-07-19 at 01:16.","The student, Seung Byum Seo, submitted this Thesis for approval on 2022-07-20 at 00:13.","This Thesis was approved for publication on 2022-07-21 at 15:54.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18373 on 2022-11-15 at 21:40:35","While there have been advances in Natural Language Processing (NLP), their success is mainly gained by applying a self-attention mechanism into single or multi-modalities. While this approach has brought significant improvements in multiple downstream tasks, it fails to capture the interaction between different entities. Therefore, we propose MM-GATBT, a multimodal graph representation learning model that captures not only the relational semantics within one modality but also the interactions between different modalities. Specifically, the proposed method constructs image-based node embedding which contains relational semantics of entities. Our empirical results show that MM-GATBT achieves state-of-the-art results among all published papers on the MM-IMDb dataset."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/116119"],"dc:language":["en","eng"],"dc:rights":["Copyright 2022 Seung Byum Seo"],"dc:subject":["multimodal learning","representation learning","graph neural network","natural language processing"],"dc:title":["Towards image-based node embedding: A novel approach for enriching multimodal representation"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Applied Mathematics"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:55Z"}