Knowledge-Based Query Expansion over a Medical Terminology Oriented Ontology on the Web

Soualmia, Lina Fatima; Barry, Catherine; Darmoni, Stéfan Jacques

doi:10.1007/978-3-540-39907-0_29

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Query Expansion Based On Domain Ontology1

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“…We have already several perspectives tracks, in particular the optimization of the Doc’CISMeF search tool to allow ‘intelligent information retrieval’. A PhD candidate (LS) developed in particular the following KnowQuE (Knowledge‐based Query Expansion) prototype system 18 which includes:…”

Section: Discussionmentioning

confidence: 99%

Enhancing the MeSH thesaurus to retrieve French online health resources in a quality‐controlled gateway

Douyère

Soualmia

Névéol

et al. 2004

Health Info Libraries J

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Section: Discussionmentioning

confidence: 99%

Enhancing the MeSH thesaurus to retrieve French online health resources in a quality‐controlled gateway

Douyère

Soualmia

Névéol

et al. 2004

Health Info Libraries J

Self Cite

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“…After word segmentation and stop words removing, the initial keywords set Q = {q 1 , q 2 , …, q n } is gained from the user's query statement. Then all the keywords in Q are mapped to the ontology concepts, and query expansion can be executed according to the interrelationships of concepts in ontology [5][6]. Advanced Printing and Packaging Materials and Technologies…”

Section: Query Expansion Based On Domain Ontologymentioning

confidence: 99%

A Study of Semantic Query Expansion Based on Domain Ontology and Local Co-Occurrence Probability Model

Ning

Wang

et al. 2015

AMM

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Keyword-based online book retrieval can not fully understand the user's query intent. Query expansion is a typical solution, but the rate of recall and precision is still very low in existing methods. In response to these problems, this paper presents a semantic query expansion method based on domain ontology and local co-occurrence probability model. First, ontology reasoning and concepts related calculation are used to obtain the initial expansion terms. Furthermore, the local co-occurrence probability model is used to filter the candidate expansion terms and the filtering function is used for secondary selection. Experiment results show that this method can effectively improve retrieval efficiency.

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Combining Knowledge-Based Methods to Refine and Expand Queries in Medicine

Soualmia

Darmoni

2004

Flexible Query Answering Systems

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Knowledge-Based Query Expansion over a Medical Terminology Oriented Ontology on the Web

Cited by 3 publications

References 9 publications

Enhancing the MeSH thesaurus to retrieve French online health resources in a quality‐controlled gateway

Enhancing the MeSH thesaurus to retrieve French online health resources in a quality‐controlled gateway

A Study of Semantic Query Expansion Based on Domain Ontology and Local Co-Occurrence Probability Model

Combining Knowledge-Based Methods to Refine and Expand Queries in Medicine

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