Papers by Lorena Calvo Bartolomé

2 papers
CASE: Large Scale Topic Exploitation for Decision Support Systems (2025.coling-demos)

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Challenge: Topic models are still a major tool for information retrieval and summarization, but their integration into decision-making systems is limited.
Approach: They propose a tool for exploiting topic information for semantic analysis of large corpora using a Solr engine and a customized indexing strategy.
Outcome: The proposed approach can be used to analyze large corpora and perform thematic trend analysis, topic-based document retrieval, or similarity search.
ITMT: Interactive Topic Model Trainer (2023.eacl-demo)

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Challenge: Topic Modeling is a commonly used technique for analyzing unstructured data, but achieving accurate results and useful models can be challenging.
Approach: They propose to use an interactive topic model trainer to train and curation topic extraction libraries and compare it with other tools for topic modeling analysis.
Outcome: The proposed tool is compared with other tools for topic modeling analysis.

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