MapIntel: Enhancing Competitive Intelligence Acquisition Through Embeddings and Visual Analytics

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)
13 Downloads (Pure)

Abstract

Competitive 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 neighbors to the query embedding and then sifts the results through a cross-encoder model that identifies the most relevant documents. The browsing module also leverages the embeddings by projecting them onto two dimensions while preserving the original landscape, resulting in a map where semantically related documents form topical clusters which we capture using topic modeling. This map aims at promoting a fast overview of the corpus while allowing a more detailed exploration and interactive information encountering process. In this work, we evaluate the system and its components on the 20 newsgroups dataset and demonstrate the superiority of Transformer-based components.

Original languageEnglish
Title of host publicationProgress in Artificial Intelligence
Subtitle of host publication21st EPIA Conference on Artificial Intelligence, EPIA 2022, Lisbon, Portugal, August 31–September 2, 2022, Proceedings
EditorsGoreti Marreiros, Bruno Martins, Ana Paiva, Alberto Sardinha, Bernardete Ribeiro
PublisherSpringer Science and Business Media Deutschland GmbH
Pages599-610
Number of pages12
ISBN (Electronic)978-3-031-16474-3
ISBN (Print)978-3-031-16473-6
DOIs
Publication statusPublished - 13 Sept 2022
Event21st EPIA Conference on Artificial Intelligence, EPIA 2022 - Lisbon, Portugal
Duration: 31 Aug 20222 Sept 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13566 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st EPIA Conference on Artificial Intelligence, EPIA 2022
Country/TerritoryPortugal
CityLisbon
Period31/08/222/09/22

Keywords

  • Competitive Intelligence
  • Information retrieval
  • Sentence embeddings
  • Topic modeling
  • Transformer architecture
  • Visual analytics

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