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MAPINTEL – Interactive visual analytics platform for competitive intelligence, 2019

Topo Projetos

About the Project

MAPINTEL - Interactive visual analytics platform for competitive intelligence

Competitive Intelligence (CI) is crucial for AICEP (Agência para o Investimento e Comércio Externo de Portugal) to promote Portuguese exports and secure foreign direct investment. CI involves analyzing vast amounts of unstructured text data, such as news, reports, and announcements, to support strategic planning and decision-making. This data is challenging to process manually, making timely and accurate responses difficult.

To address this, the MAPINTEL project developed a neural network-based document clustering system. Using Self-Organizing Maps (SOMs) and advanced algorithms like doc2vec, this system efficiently extracts and organizes valuable information. The interactive visual analytics tool, MapIntel, enhances AICEP's ability to respond strategically to global events affecting Portuguese exports and investment.

 

Our contribution

NOVA IMS coordinated all research activities in the MAPINTEL project, focusing on developing the intelligent system to support AICEP’s competitive intelligence efforts. We began by preparing and defining the data requirements, ensuring a solid foundation for the project. Our team then developed a neural network-based document clustering system using advanced algorithms, including Self-Organizing Maps (SOMs) and doc2vec for text feature extraction.

This neural approach allowed us to map documents as points on a semantic map, preserving the topological order and capturing the similarity of their contents. By integrating these maps into an interactive visual analytics tool, we facilitated the efficient exploration and retrieval of relevant documents. Users could engage with the data through various interactive methods, such as point-and-click, brushing, linking between views, and using prototype examples for targeted searches.

Partnership

  • AICEP Portugal Global

Contribution to the SDGs

  • SDG 8
  • SDG 9 Industry, Innovation, And Infrastructure
  • SDG 16

Funding

  • Funding Programme: FCT, I.P. - Scientific Research and Technological Development Projects in Data Science and Artificial Intelligence in Public Administration - 2019
  • Funding to NOVA IMS: 44.450,00 €
  • Duration: 2019 - 2021

Project outputs

  • "MapIntel: A visual analytics platform for competitive intelligence. Expert Systems, [e13445]"

    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

  • "Public Procurement Fraud Detection: A Review Using Network Analysis"

    Lyra, M. S., Pinheiro, F. L., & Bacao, F. (2022)

    Public Procurement Fraud Detection: A Review Using Network Analysis. In R. M. Benito, C. Cherifi, H. Cherifi, E. Moro, L. M. Rocha, & M. Sales-Pardo (Eds.), Complex Networks & Their Applications X: Proceedings of the Tenth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021 (Vol. 1) (Vol. I, pp. 116-129). (Studies in Computational Intelligence; Vol. 1015). Springer, Cham. https://doi.org/10.1007/978-3-030-93409-5_11

  • "G-SOMO: An oversampling approach based on self-organized maps and geometric SMOTE"

    Douzas, G., Rauch, R., & Bacao, F. (2021)

    G-SOMO: An oversampling approach based on self-organized maps and geometric SMOTE. Expert Systems with Applications, 183, 1-11. [115230]. https://doi.org/10.1016/j.eswa.2021.115230.

  • "Improving the quality of predictive models in small data GSDOT: A new algorithm for generating synthetic data"

    Fonseca, J., & Bação, F. (2023)

    Improving Active Learning Performance through the Use of Data Augmentation. International Journal of Intelligent Systems, 2023, 1-17. https://doi.org/10.1155/2023/7941878.

     

  • "Improving Active Learning Performance through the Use of Data Augmentation"

    Fonseca, J., & Bação, F. (2023)

    Improving Active Learning Performance through the Use of Data Augmentation. International Journal of Intelligent Systems, 2023, 1-17. https://doi.org/10.1155/2023/7941878.

  • "Tabular and latent space synthetic data generation: a literature review"

    Fonseca, J., & Bacao, F. (2023)

    Tabular and latent space synthetic data generation: a literature review. Journal of Big Data, 10, 1-37. [115]. https://doi.org/10.1186/s40537-023-00792-7.

  • "Topic Modeling: A Consistent Framework for Comparative Studies"

    Amaro, A., & Bação, F. (2024)

    Topic Modeling: A Consistent Framework for Comparative Studies. Emerging Science Journal, 8(1), 125-139. https://doi.org/10.28991/ESJ-2024-08-01-09.

  • "Characterization of the Firm-Firm Public Procurement Co-Bidding Network from the State of Ceará (Brazil) Municipalities"

    Lyra, M. D. S., Curado, A., Damásio, B., Bação, F., & Pinheiro, F. L. (2021)

    Characterization of the Firm-Firm Public Procurement Co-Bidding Network from the State of Ceará (Brazil) Municipalities. Applied Network Science, 6, 1-10. [77]. https://doi.org/10.1007/s41109-021-00418-y.

     

  • "A Rapid Semi-automated Literature Review on Legal Precedents Retrieval"

    Silva, H., António, N., & Bacao, F. (2022)

    A Rapid Semi-automated Literature Review on Legal Precedents Retrieval. In G. Marreiros, B. Martins, A. Paiva, B. Ribeiro, & A. Sardinha (Eds.), Progress in Artificial Intelligence: 21st  EPIA Conference on Artificial Intelligence, EPIA 2022, Lisbon, Portugal, August 31–September 2, 2022, Proceedings (pp. 53-65). (Lecture Notes in Artificial Intelligence; Vol. 13566). Springer, Cham. https://doi.org/10.1007/978-3-031-16474-3_5.

  • "Triplet extraction leveraging sentence transformers and dependency parsing"

    Silva, D., & Bacao, F. (2022)

    MapIntel: Enhancing Competitive Intelligence Acquisition Through Embeddings and Visual Analytics. In G. Marreiros, B. Martins, A. Paiva, A. Sardinha, & B. Ribeiro (Eds.), Progress in Artificial Intelligence: 21st  EPIA Conference on Artificial Intelligence, EPIA 2022, Lisbon, Portugal, August 31–September 2, 2022, Proceedings (pp. 599-610). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13566 LNAI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-16474-3_49.