{"id":{"repo_id":"southwales","oai_identifier":"oai:pure.atira.dk:studenttheses/9d52ba01-2abe-41f7-9aa2-2c437e8454fc"},"canonical_url":"https://search.dev.ndltd.org/etd/southwales/oai:pure.atira.dk:studenttheses/9d52ba01-2abe-41f7-9aa2-2c437e8454fc","repository":{"repo_id":"southwales","name":"University of South Wales","base_url":"https://pure.southwales.ac.uk/ws/oai"},"display":{"title":"Improving Entity Based Information Retrieval In Video","abstract":"This PhD by project portfolio advances entity-based information retrieval in video, enabling deep search across multi-modal media in the e-commerce sector. Based in applied industrial research, the resulting work led to several granted technology patents that form a commercial system. The system allows organizations to identify and extract information from video content that was previously challenging to access. The portfolio describes three interconnected projects within a single system designed to extract and provide actionable commercial and industry intelligence at scale. The first project focuses on automatically segmenting and extracting data from webpages, creating a mapping database essential for entity normalization. The second project identifies and classifies key components within video, such as objects, people and brands; these are then aligned across different modalities. Having such topics of interest pre-identified helps reduce the subsequent search space. Finally, the third project details a process for entity normalization through a multi-modal approach to brand and product identification, significantly improving search accuracy. Collectively, these projects enhance brand, logo, sentiment and topic detection, offering a robust foundation for future development in video-based information retrieval.","abstract_html":"This PhD by project portfolio advances entity-based information retrieval in video, enabling deep search across multi-modal media in the e-commerce sector. Based in applied industrial research, the resulting work led to several granted technology patents that form a commercial system. The system allows organizations to identify and extract information from video content that was previously challenging to access. The portfolio describes three interconnected projects within a single system designed to extract and provide actionable commercial and industry intelligence at scale. The first project focuses on automatically segmenting and extracting data from webpages, creating a mapping database essential for entity normalization. The second project identifies and classifies key components within video, such as objects, people and brands; these are then aligned across different modalities. Having such topics of interest pre-identified helps reduce the subsequent search space. Finally, the third project details a process for entity normalization through a multi-modal approach to brand and product identification, significantly improving search accuracy. Collectively, these projects enhance brand, logo, sentiment and topic detection, offering a robust foundation for future development in video-based information retrieval.","abstract_has_math":false,"creators":["O'Neill, Allen"],"institution":null,"degree_name":"Doctoral Thesis","degree_level":"Student thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Wilson, Ian","Ware, Jonathan"],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026","date_published":"2026","updated_at":"2026-07-24T04:40:03Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:pure.atira.dk:studenttheses/9d52ba01-2abe-41f7-9aa2-2c437e8454fc"],"render_values":[{"text":"oai:pure.atira.dk:studenttheses/9d52ba01-2abe-41f7-9aa2-2c437e8454fc","href":null,"code":true}]}]},"links":{"outbound_url":"https://pure.southwales.ac.uk/en/studentTheses/9d52ba01-2abe-41f7-9aa2-2c437e8454fc","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Wilson, Ian","Ware, Jonathan"]},{"key":"dc:creator","label":"Author","values":["O'Neill, Allen"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2026"]},{"key":"dc:date.issued","label":"Date","values":["2026"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://pure.southwales.ac.uk/en/studentTheses/9d52ba01-2abe-41f7-9aa2-2c437e8454fc"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Student thesis"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctoral Thesis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:pure.atira.dk:studenttheses/9d52ba01-2abe-41f7-9aa2-2c437e8454fc","https://pure.southwales.ac.uk/en/studentTheses/9d52ba01-2abe-41f7-9aa2-2c437e8454fc"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://pure.southwales.ac.uk/files/36690823/Allen_ONeill_-_PhD_Thesis_-_Final.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This PhD by project portfolio advances entity-based information retrieval in video, enabling deep search across multi-modal media in the e-commerce sector. Based in applied industrial research, the resulting work led to several granted technology patents that form a commercial system. The system allows organizations to identify and extract information from video content that was previously challenging to access. The portfolio describes three interconnected projects within a single system designed to extract and provide actionable commercial and industry intelligence at scale. The first project focuses on automatically segmenting and extracting data from webpages, creating a mapping database essential for entity normalization. The second project identifies and classifies key components within video, such as objects, people and brands; these are then aligned across different modalities. Having such topics of interest pre-identified helps reduce the subsequent search space. Finally, the third project details a process for entity normalization through a multi-modal approach to brand and product identification, significantly improving search accuracy. Collectively, these projects enhance brand, logo, sentiment and topic detection, offering a robust foundation for future development in video-based information retrieval."]},{"key":"dc:title","label":"Title","values":["Improving Entity Based Information Retrieval In Video"]}]}],"canonical_facts":{"dc:contributor.advisor":["Wilson, Ian","Ware, Jonathan"],"dc:creator":["O'Neill, Allen"],"dc:date":["2026"],"dc:date.issued":["2026"],"dc:description.abstract":["This PhD by project portfolio advances entity-based information retrieval in video, enabling deep search across multi-modal media in the e-commerce sector. Based in applied industrial research, the resulting work led to several granted technology patents that form a commercial system. The system allows organizations to identify and extract information from video content that was previously challenging to access. The portfolio describes three interconnected projects within a single system designed to extract and provide actionable commercial and industry intelligence at scale. The first project focuses on automatically segmenting and extracting data from webpages, creating a mapping database essential for entity normalization. The second project identifies and classifies key components within video, such as objects, people and brands; these are then aligned across different modalities. Having such topics of interest pre-identified helps reduce the subsequent search space. Finally, the third project details a process for entity normalization through a multi-modal approach to brand and product identification, significantly improving search accuracy. Collectively, these projects enhance brand, logo, sentiment and topic detection, offering a robust foundation for future development in video-based information retrieval."],"dc:identifier":["oai:pure.atira.dk:studenttheses/9d52ba01-2abe-41f7-9aa2-2c437e8454fc","https://pure.southwales.ac.uk/en/studentTheses/9d52ba01-2abe-41f7-9aa2-2c437e8454fc"],"dc:identifier.uri":["https://pure.southwales.ac.uk/files/36690823/Allen_ONeill_-_PhD_Thesis_-_Final.pdf"],"dc:language":["eng"],"dc:relation.isreferencedby":["https://pure.southwales.ac.uk/en/studentTheses/9d52ba01-2abe-41f7-9aa2-2c437e8454fc"],"dc:title":["Improving Entity Based Information Retrieval In Video"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["Student thesis"],"dc:type.qualificationname":["Doctoral Thesis"]},"updated_at":"2026-07-24T04:40:03Z"}