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Gismo : Mettez un tigre dans votre moteur

Abstract : Searching for documents is a task that everyone faces on a regular basis, especially when looking for a relevant Internet page, an e-mail, or a document on an Intranet. An effective search relies on a precise and well-organized search engine. The majority of current techniques combine a keyword search with structural information (ontologies, relationships between elements) in order to order the documents in a corpus by relevance. In this article, we present a new navigation engine called Gismo (Generic Information Search with a Mind of its Own). Gismo exploits only the textual content of documents and does not require ontology, metadata, or prelearning. It is thus possible to use it on any corpus without making assumptions about the type of documents or their language. The model chosen and the algorithms used allow Gismo to be extremely fast even on large corpora. Finally, Gismo allows you to find, sort and organize documents by theme and relevance, making it an navigation engine and not a simple search engine.
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Contributor : Fabien Mathieu <>
Submitted on : Wednesday, June 24, 2020 - 9:28:29 PM
Last modification on : Thursday, December 10, 2020 - 11:00:43 AM


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  • HAL Id : hal-02880360, version 1


Marc-Olivier Buob, Fabien Mathieu. Gismo : Mettez un tigre dans votre moteur. ALGOTEL 2020 – 22èmes Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications, Sep 2020, Lyon, France. ⟨hal-02880360⟩



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