MapIntel

Detalhes bibliográficos
Autor(a) principal: Silva, David
Data de Publicação: 2023
Outros Autores: Bação, Fernando
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10362/158052
Resumo: Silva, D., & Bação, F. (2023). MapIntel: A visual analytics platform for competitive intelligence. Expert Systems, [e13445]. https://doi.org/https://www.authorea.com/doi/full/10.22541/au.166785335.50477185, https://doi.org/10.1111/exsy.13445 --- %ABS2% ---Funding Information: This work was supported by the (research grant under the DSAIPA/DS/0116/2019 project). Fundação para a Ciência e Tecnologia of Ministério da Ciência e Tecnologia e Ensino Superior
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spelling MapIntelA visual analytics platform for competitive intelligencecompetitive intelligenceinformation retrievalsentence embeddingstopic modellingtransformer architecturevisual analyticsControl and Systems EngineeringTheoretical Computer ScienceComputational Theory and MathematicsArtificial IntelligenceSilva, D., & Bação, F. (2023). MapIntel: A visual analytics platform for competitive intelligence. Expert Systems, [e13445]. https://doi.org/https://www.authorea.com/doi/full/10.22541/au.166785335.50477185, https://doi.org/10.1111/exsy.13445 --- %ABS2% ---Funding Information: This work was supported by the (research grant under the DSAIPA/DS/0116/2019 project). Fundação para a Ciência e Tecnologia of Ministério da Ciência e Tecnologia e Ensino SuperiorCompetitive Intelligence allows an organization to keep up with market trends and foresee business opportunities. This practice is mainly performed by analysts scanning for any piece of valuable information in a myriad of dispersed and unstructured sources. Here we present MapIntel, a system for acquiring intelligence from vast collections of text data by representing each document as a multidimensional vector that captures its own semantics. The system is designed to handle complex Natural Language queries and visual exploration of the corpus, potentially aiding overburdened analysts in finding meaningful insights to help decision-making. The system searching module uses a retriever and re-ranker engine that first finds the closest neighbours to the query embedding and then sifts the results through a cross-encoder model that identifies the most relevant documents. The browsing or visualization module also leverages the embeddings by projecting them onto two dimensions while preserving the multidimensional landscape, resulting in a map where semantically related documents form topical clusters which we capture using topic modelling. This map aims at promoting a fast overview of the corpus while allowing a more detailed exploration and interactive information encountering process. We evaluate the system and its components on the 20 newsgroups data set, using the semantic document labels provided, and demonstrate the superiority of Transformer-based components. Finally, we present a prototype of the system in Python and show how some of its features can be used to acquire intelligence from a news article corpus we collected during a period of 8 months.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNSilva, DavidBação, Fernando2024-12-28T01:31:54Z2023-122023-12-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article17application/pdfapplication/pdfhttp://hdl.handle.net/10362/158052eng0266-4720PURE: 72008278https://doi.org/10.22541/au.166785335.50477185info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-12-30T01:34:17Zoai:run.unl.pt:10362/158052Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:45:05.585819Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv MapIntel
A visual analytics platform for competitive intelligence
title MapIntel
spellingShingle MapIntel
Silva, David
competitive intelligence
information retrieval
sentence embeddings
topic modelling
transformer architecture
visual analytics
Control and Systems Engineering
Theoretical Computer Science
Computational Theory and Mathematics
Artificial Intelligence
title_short MapIntel
title_full MapIntel
title_fullStr MapIntel
title_full_unstemmed MapIntel
title_sort MapIntel
author Silva, David
author_facet Silva, David
Bação, Fernando
author_role author
author2 Bação, Fernando
author2_role author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Silva, David
Bação, Fernando
dc.subject.por.fl_str_mv competitive intelligence
information retrieval
sentence embeddings
topic modelling
transformer architecture
visual analytics
Control and Systems Engineering
Theoretical Computer Science
Computational Theory and Mathematics
Artificial Intelligence
topic competitive intelligence
information retrieval
sentence embeddings
topic modelling
transformer architecture
visual analytics
Control and Systems Engineering
Theoretical Computer Science
Computational Theory and Mathematics
Artificial Intelligence
description Silva, D., & Bação, F. (2023). MapIntel: A visual analytics platform for competitive intelligence. Expert Systems, [e13445]. https://doi.org/https://www.authorea.com/doi/full/10.22541/au.166785335.50477185, https://doi.org/10.1111/exsy.13445 --- %ABS2% ---Funding Information: This work was supported by the (research grant under the DSAIPA/DS/0116/2019 project). Fundação para a Ciência e Tecnologia of Ministério da Ciência e Tecnologia e Ensino Superior
publishDate 2023
dc.date.none.fl_str_mv 2023-12
2023-12-01T00:00:00Z
2024-12-28T01:31:54Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/158052
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0266-4720
PURE: 72008278
https://doi.org/10.22541/au.166785335.50477185
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eu_rights_str_mv openAccess
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