Dans cette thèse, nous nous intéressons aux relations qui peuvent exister entre des prédicats verbaux(ex : to regulate) et des prédicats nominaux (ex : regulation) dont les structures argumentales mettent enjeu des informations communes. Nous nous livrons à une formalisation des conditions dans lesquelles se réalisent des relations d’équivalence entre les constructions verbales et nominales. La mise en évidence de l’équivalence des structures argumentales de ces deux types de constructions est fondamentale pour pouvoir réaliser, par exemple, des systèmes d’extraction automatique d’informations très performants. En se basant sur les données du lexique The Specialist Lexicon, nous proposons une prédiction raisonnable du comportement syntaxique des arguments nominaux, de différents groupes nominaux prédicatifs(GNpréd), lorsqu’ils sont en position de postmodifieur. Cette étude nous a conduit à concevoir un ensemble d’algorithmes et à développer une plate-forme, Predicate DB, qui nous a permis de produire un lexique de nominalisations. Pour chaque entrée appartenant à ce lexique, nous avons caractérisé ses structures argumentales et ses réalisations dans des GNpréd dont les arguments sont marqués par des prépositions spécifiques. / In this thesis, we focus on the relation that may exist between verbal predicates (e.g., regulate)and nominal predicates (e.g., regulation) whose argument structures involve common information.We make a formalization of the conditions in which equivalent relations between verbal and nominalconstructions are carried out. Bringing out the equivalence of argument structures between these twotypes of constructions is fundamental for achieving, for example, very efficient Information Extractionsystems. Based on data from the Specialist Lexicon, we propose a reasonable prediction of the syntacticbehavior of nominal arguments, which belong to different predicate noun phrases (PNPs), when theyare in postmodifier position. This study has led us to design a set of algorithms and develop a platform,PredicateDB, to produce a lexicon of nominalizations. For each entry belonging to this lexicon, we havedefined its argument structures and achievements in PNPs whose arguments are marked by specificprepositions.

In this thesis a natural language query interface is developed for semantic and spatio-temporal querying of MPEG-7 based domain ontologies. The underlying ontology is created by attaching domain ontologies to the core Rhizomik MPEG-7 ontology. The user can pose concept, complex concept (objects connected with an &ldquo / AND&rdquo / or &ldquo / OR&rdquo / connector), spatial (left, right . . . ), temporal (before, after, at least 10 minutes before, 5 minutes after . . . ), object trajectory and directional trajectory (east, west, southeast . . . , left, right, upwards . . . ) queries to the system. Furthermore, the system handles the negative meaning in the user input. When the user enters a natural language (NL) input, it is parsed with the link parser. According to query type, the objects, attributes, spatial relation, temporal relation, trajectory relation, time filter and time information are extracted from the parser output by using predefined rules. After the information extraction, SPARQL queries are generated, and executed against the ontology by using an RDF API. Results are retrieved and they are used to calculate spatial, temporal, and trajectory relations between objects. The results satisfying the required relations are displayed in a tabular format and user can navigate through the multimedia content.

The video databases and retrieval of data from these databases have become popular in various business areas of work with the improvements in technology. As a kind of video database, video archive systems need user-friendly interfaces to retrieve video frames. In this thesis, an NLP based user interface to a video database system is developed using a content-based spatio-temporal video data model. The data model is focused on the semantic content which includes objects, activities, and spatial properties of objects. Spatio-temporal relationships between video objects and also trajectories of moving objects can be queried with this data model. In this video database system, NL interface enables flexible querying. The queries, which are given as English sentences, are parsed using Link Parser. Not only exact matches but similar objects and activities are also returned from the database with the help of the conceptual ontology module to return all related frames to the user. This module is implemented using a distance-based method of semantic similarity search on the semantic domain-independent ontology, WordNet. The semantic representations of the given queries are extracted from their syntactic structures using information extraction techniques. The extracted semantic representations are used to call the related parts of the underlying spatio-temporal video data model to calculate the results of the queries.