Subontology Extraction Using Hyponym and Hypernym Closure on is-a Directed Acyclic Graphs

International audienceOntologies are successfully used as semantic guides when navigating through the huge and ever increasing quantity of digital documents. Nevertheless, the size of numerous domain ontologies tends to grow beyond the human capacity to grasp information. This growth is problematic for a lot of key applications that require user interactions such as document annotation or ontology modification/evolution. The problem could be partially overcome by providing users with a sub-ontology focused on their current concepts of interest. A sub-ontology restricted to this sole set of concepts is of limited interest since their relationships can generally not be explicit without adding some of their hyponyms and hypernyms. This paper proposes efficient algorithms to identify these additional key concepts based on the closure of two common graph operators: the least common-ancestor and greatest common descendant. The resulting method produces ontology excerpts focused on a set of concepts of interest and is fast enough to be used in interactive environments. As an example, we use the resulting program, called OntoFocus (http://www.ontotoolkit.mines-ales.fr/), to restrict, in few seconds, the large Gene Ontology (~30,000 concepts) to a sub-ontology focused on concepts annotating a gene related to breast cancer

User Centered and Ontology Based InformationRetrieval System for Life Sciences

Because of the increasing number of electronic data, designing efficient tools to retrieve and exploit documents is a major challenge. Current search engines suffer from two main drawbacks: there is limited interaction with the list of retrieved documents and no explanation for their adequacy to the query. Users may thus be confused by the selection and have no idea how to adapt their query so that the results match their expectations. 
This talk describes a request method and an environment based on aggregating models to assess the relevance of documents annotated by concepts of ontology. The selection of documents is then displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user’s query; this man/machine interface favors a more interactive exploration of data corpus.
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OBIRS-feedback, une méthode de reformulation utilisant une ontologie de domaine

National audienceLes performances d'un système de recherche d'information (SRI) peuvent être dégradées en termes de précision du fait de la difficulté pour des utilisateurs à formuler précisément leurs besoins en information. La reformulation ou l'expansion de requêtes constitue une des réponses à ce problème dans le cadre des SRI. Dans cet article, nous proposons une nouvelle méthode de reformulation de requêtes conceptuelles qui, à partir de documents jugés pertinents par l'utilisateur et d'une ontologie de domaine, cherche un ensemble de concepts maximisant les performances du SRI. Celles-ci sont évaluées, de manière originale, à l'aide d'indicateurs dont une formalisation est proposée. Cette méthode a été évaluée en utilisant notre moteur OBIRS, l'ontologie de domaine MeSH et la collection de tests MuCHMORE

USI: a fast and accurate approach for conceptual document annotation

International audienceBackground : Semantic approaches such as concept-based information retrieval rely on a corpus in which resources are indexed by concepts belonging to a domain ontology. In order to keep such applications up-to-date, new entities need to be frequently annotated to enrich the corpus. However, this task is time-consuming and requires a high-level of expertise in both the domain and the related ontology. Different strategies have thus been proposed to ease this indexing process, each one taking advantage from the features of the document.Results : In this paper we present USI (User-oriented Semantic Indexer), a fast and intuitive method for indexing tasks. We introduce a solution to suggest a conceptual annotation for new entities based on related already indexed documents. Our results, compared to those obtained by previous authors using the MeSH thesaurus and a dataset of biomedical papers, show that the method surpasses text-specific methods in terms of both quality and speed. Evaluations are done via usual metrics and semantic similarity.Conclusions : By only relying on neighbor documents, the User-oriented Semantic Indexer does not need a representative learning set. Yet, it provides better results than the other approaches by giving a consistent annotation scored with a global criterion instead of one score per concept

Actes des 29es Journées Francophones d'Ingénierie des Connaissances, IC 2018

International audienc

How ontology based information retrieval systems may benefit from lexical text analysis

International audienceThe exponential growth of available electronic data is almost useless without efficient tools to retrieve the right information at the right time. It is now widely acknowledged that information retrieval systems need to take semantics into account to enhance the use of available information. However, there is still a gap between the amounts of relevant information that can be accessed through optimized IRSs on the one hand, and users' ability to grasp and process a handful of relevant data at once on the other. This chapter shows how conceptual and lexical approaches may be jointly used to enrich document description. After a survey on semantic based methodologies designed to efficiently retrieve and exploit information, hybrid approaches are discussed. The original approach presented here benefits from both lexical and ontological document description, and combines them in a software architecture dedicated to information retrieval and rendering in specific domains

OrthoMaM: A database of orthologous genomic markers for placental mammal phylogenetics

<p>Abstract</p> <p>Background</p> <p>Molecular sequence data have become the standard in modern day phylogenetics. In particular, several long-standing questions of mammalian evolutionary history have been recently resolved thanks to the use of molecular characters. Yet, most studies have focused on only a handful of standard markers. The availability of an ever increasing number of whole genome sequences is a golden mine for modern systematics. Genomic data now provide the opportunity to select new markers that are potentially relevant for further resolving branches of the mammalian phylogenetic tree at various taxonomic levels.</p> <p>Description</p> <p>The EnsEMBL database was used to determine a set of orthologous genes from 12 available complete mammalian genomes. As targets for possible amplification and sequencing in additional taxa, more than 3,000 exons of length > 400 bp have been selected, among which 118, 368, 608, and 674 are respectively retrieved for 12, 11, 10, and 9 species. A bioinformatic pipeline has been developed to provide evolutionary descriptors for these candidate markers in order to assess their potential phylogenetic utility. The resulting OrthoMaM (Orthologous Mammalian Markers) database can be queried and alignments can be downloaded through a dedicated web interface <url>http://kimura.univ-montp2.fr/orthomam</url>.</p> <p>Conclusion</p> <p>The importance of marker choice in phylogenetic studies has long been stressed. Our database centered on complete genome information now makes possible to select promising markers to a given phylogenetic question or a systematic framework by querying a number of evolutionary descriptors. The usefulness of the database is illustrated with two biological examples. First, two potentially useful markers were identified for rodent systematics based on relevant evolutionary parameters and sequenced in additional species. Second, a complete, gapless 94 kb supermatrix of 118 orthologous exons was assembled for 12 mammals. Phylogenetic analyses using probabilistic methods unambiguously supported the new placental phylogeny by retrieving the monophyly of Glires, Euarchontoglires, Laurasiatheria, and Boreoeutheria. Muroid rodents thus do not represent a basal placental lineage as it was mistakenly reasserted in some recent phylogenomic analyses based on fewer taxa. We expect the OrthoMaM database to be useful for further resolving the phylogenetic tree of placental mammals and for better understanding the evolutionary dynamics of their genomes, i.e., the forces that shaped coding sequences in terms of selective constraints.</p

From Theoretical Framework To Generic Semantic Measures Library

International audienceThanks to the ever-increasing use of the Semantic Web, a growing number of entities (e.g. documents) are characterized by non-ambiguous mean-ings. Based on this characterization, entities can subsequently be compared us-ing semantic measures. A plethora of measures have been designed given their critical importance in numerous treatments relying on ontologies. However, the improvement and use of semantic measures are currently hampered by the lack of a dedicated theoretical framework and an extensive generic software solution dedicated to them. To meet these needs, this paper presents a unified theoretical framework of graph-based semantic measures, from which we developed the open source Semantic Measures Library and toolkit; a solution that paves the way for straightforward design, computation and analysis of semantic measures for both users and developers. Downloads, documentation and technical support at dedicated website http://www.semantic-measures-library.org