rania soussi - Academia.edu (original) (raw)
Papers by rania soussi
Les cahiers du numérique, Sep 30, 2015
Le projet Campus AAR est un projet qui a comme objectif de constituer et exploiter des patrimoine... more Le projet Campus AAR est un projet qui a comme objectif de constituer et exploiter des patrimoines scientifiques des sciences humaines et sociales sous forme d’archives audiovisuelles numeriques. Ceci est mis en place a travers une plateforme logicielle appelee Studio Campus AAR qui permet a un detenteur d’archives d’analyser, exposer, republier, rechercher et rendre interoperables des ressources audiovisuelles. Dans cet article, l’environnement de publication de ce studio est presente. Le processus de publication est base sur des technologies du web semantique afin d’assister les auteurs a creer d’une maniere autonome leurs publications.
HAL (Le Centre pour la Communication Scientifique Directe), Dec 1, 2008
With the continual increase of the volume of available information on the web, information access... more With the continual increase of the volume of available information on the web, information access and knowledge management become challenging. Thus, adding a semantic dimension to the Web, by the deployment of ontologies, contributes to solve many problems. In the context of the semantic Web, ontologies improve the exploitation of Web resources by adding a consensual field of knowledge. The need for using domain ontology for information retrieval (IR) has been explored by some approaches to better answer users' queries. However, ontology in IR system requires a regular updating, especially the addition of new concepts and relationships. In fact, IR systems are generally based on few number of domain ontology that cannot be extended. This paper proposes an incremental approach for domain ontology learning. This approach is designed to be integrated into IR system based on ontology. It is based on an ontological representation called "Metaontology." The approach presented was tested and evaluated on a tourism ontology built from results of an online IR system based on ontology.
Lecture Notes in Computer Science, 2012
ABSTRACT In the enterprise context, people need to visualize different types of interactions betw... more ABSTRACT In the enterprise context, people need to visualize different types of interactions between heterogeneous objects in order to make the right decision. Therefore, we have proposed, in previous works, an approach of enterprise object graphs extraction which describes these interactions. One of the steps involved in this approach consists in identifying automatically the enterprise objects. Since the enterprise ontology has been used for describing enterprise objects and processes, we propose to integrate it in this process. The main contribution of this work is to propose an approach for enterprise ontology learning coping with both generic and specific aspects of enterprise information. It is three-folded: First, general enterprise ontology is semi-automatically built in order to represent general aspects. Second, ontology learning method is applied to enrich and populate this latter with specific aspects. Finally, the resulting ontology is used to identify objects in the graph extraction process.
HAL (Le Centre pour la Communication Scientifique Directe), Mar 12, 2008
La croissance très importante des informations disponibles sur Internet nécessite des outils de r... more La croissance très importante des informations disponibles sur Internet nécessite des outils de recherche de plus en plus performants permettant de discerner efficacement les informations intéressantes parmi des centaines voire des milliers de documents. Seulement, la qualité des résultats fournis par les moteurs de recherche traditionnels n'est pas toujours pertinente surtout quand il s' agit de composer plus d'une requête. Ceci est dû aux ambiguïtés linguistiques et aux concepts abstraits qui ne sont pas bien traités. L'utilisation ...
Lecture Notes in Computer Science, 2012
An adapted modeling and visualization technique of links and interactions between several objects... more An adapted modeling and visualization technique of links and interactions between several objects,e.g. customers and products, social network and etc,is a precious mean to permit a good understanding of a lot of situations in the enterprise's context. In this latter context, most of the time, these objects and their relations are stored in relational databases. But extracting and modeling heterogeneous graphs from databases are outside of the classical graph models possibilities, moreover when each node contains a set of values. On the other hand, graph models can be a natural way to present these graphs and facilitates their query. In this way, we propose a graph model named SPIDER-Graph which is adapted to represent interactions between complex heterogeneous objects extracted from a relational database. This model is used in our approach of heterogeneous object graph extraction from a relational database which is detailed in this paper.
In the enterprise context, an important amount of information is stored in relational databases. ... more In the enterprise context, an important amount of information is stored in relational databases. Therefore, relational database can be a rich source to extract social network. Moreover, it is not very suitable to present and store a social network. On the other hand, a graph database canmodel data in natural way and facilitates the query of data using graph operations.
The huge number of available documents on the Web makes finding relevant ones challenging. Thus, ... more The huge number of available documents on the Web makes finding relevant ones challenging. Thus, searching for information becomes more and more complex because of the growing volume of data and of its lack of structure. The quality of results that traditional full-text search engines provide is still not optimal for many types of user queries. Especially, the ambiguities of natural languages and abstract concepts are handled inadequately by full-text search engines. Ontologies provide a solution to these problems. They can help a user to find documents of a specific domain. This paper proposes a new retrieval system based on ontologies. This system integrates results from traditional full-text engines, and thus supports a gradual transition from classical full-text search engines to ontology-based ones.
The present work introduces a set of solutions to extract graphs from enterprise data and facilit... more The present work introduces a set of solutions to extract graphs from enterprise data and facilitate the process of information search on these graphs. First of all we have defined a new graph model called the SPIDER-Graph, which models complex objects and permits to define heterogeneous graphs. Furthermore, we have developed a set of algorithms to extract the content of a database from an enterprise and to represent it in this new model. This latter representation allows us to discover relations that exist in the data but are hidden due to their poor compatibility with the classical relational model. Moreover, in order to unify the representation of all the data of the enterprise, we have developed a second approach which extracts from unstructured data an enterprise's ontology containing the most important concepts and relations that can be found in a given enterprise. Having extracted the graphs from the relational databases and documents using the enterprise ontology, we pro...
With the continual increase of the volume of available information on the web, information access... more With the continual increase of the volume of available information on the web, information access and knowledge management become challenging. Thus, adding a semantic dimension to the Web, by the deployment of ontologies, contributes to solve many problems. In the context of the semantic Web, ontologies improve the exploitation of Web resources by adding a consensual field of knowledge. The need for using domain ontology for information retrieval (IR) has been explored by some approaches to better answer users ’ queries. However, ontology in IR system requires a regular updating, especially the addition of new concepts and relationships. In fact, IR systems are generally based on few number of domain ontology that cannot be extended. This paper proposes an incremental approach for domain ontology learning. This approach is designed to be integrated into IR system based on ontology. It is based on an ontological representation called "Metaontology. " The approach presented ...
Data manipulated in an enterprise context are structured data as well as unstructured data such a... more Data manipulated in an enterprise context are structured data as well as unstructured data such as emails, documents, social networks, etc. Graphs are a natural way of representing and modeling such data in a unified manner (Structured, semi-structured and unstructured ones). The main advantage of such a structure relies in the dynamic aspect and the capability to represent relations, even multiple ones, between objects. Recent database research work shows a growing interest in the definition of graph models and languages to allow a natural way of handling data appearing. In this chapter, we give a survey of the main graph database models and the associated graph query languages. We then present an application using a graph database to extract social networks. Graph Database For collaborative Communities............................................... 1
MOTS-CLES : recherche d'information en ligne, construction d'ontologies ABSTRACT. The hug... more MOTS-CLES : recherche d'information en ligne, construction d'ontologies ABSTRACT. The huge number of available documents on the Web makes finding relevant ones challenging. Thus, searching for information becomes more and more complex because of the growing volume of data and of its lack of structure. The quality of results that traditional full-text search engines provide is still not optimal for many types of user queries. The ambiguities of natural languages and abstract concepts are handled inadequately by full- text search engines. Ontologies provide a solution to these problems. An architecture composed of several ontologies is proposed to represent concepts as well as services of domain. In this paper, we expose the contribution of these ontologies in information retrieval and we propose a new retrieval system based on ontologies. Experimentation in the domain of the tourism is presented, and the gotten results are compared to other systems.
Lecture Notes in Social Networks, 2012
In the enterprise context, People need to visualize different types of interactions between heter... more In the enterprise context, People need to visualize different types of interactions between heterogeneous objects (e.g. product and site, customers and product, people interaction (social network)...). The existing approaches focus on social networks extraction using web document. However a considerable amount of information is stored in relational databases. Therefore, relational databases can be seen as rich sources for extracting a social network. The extracted network has in general a huge size which makes it difficult to analyze and visualize. An aggregation step is needed in order to have more understandable graphs. In this chapter, we propose a heterogeneous object graph extraction approach from a relational database and we present its application to extract social network. This step is followed by an aggregation step in order to improve the visualisation and the analyse of the extracted social network. Then, we aggregate the resulting network using the k-SNAP algorithm which produces a summarized graph.
Actes de la 5ème conférence en Recherche d'Information et Applications.(CORIA 2008), Mar 12, 2008
La croissance très importante des informations disponibles sur Internet nécessite des outils de r... more La croissance très importante des informations disponibles sur Internet nécessite des outils de recherche de plus en plus performants permettant de discerner efficacement les informations intéressantes parmi des centaines voire des milliers de documents. Seulement, la qualité des résultats fournis par les moteurs de recherche traditionnels n'est pas toujours pertinente surtout quand il s' agit de composer plus d'une requête. Ceci est dû aux ambiguïtés linguistiques et aux concepts abstraits qui ne sont pas bien traités. L'utilisation ...
Springer eBooks, 2011
Data manipulated in an enterprise context are structured data as well as unstructured data such a... more Data manipulated in an enterprise context are structured data as well as unstructured data such as emails, documents, social networks, etc. Graphs are a natural way of representing and modeling such data in a unified manner (Structured, semi-structured and unstructured ones). The main advantage of such a structure relies in the dynamic aspect and the capability to represent relations, even multiple ones, between objects. Recent database research work shows a growing interest in the definition of graph models and languages to allow a natural way of handling data appearing. In this chapter, we give a survey of the main graph database models and the associated graph query languages. We then present an application using a graph database to extract social networks.
Extraction et Gestion des Connaissances, 2011
Dans un contexte d'entreprise, beaucoup d'informations importantes restent stockées dans des base... more Dans un contexte d'entreprise, beaucoup d'informations importantes restent stockées dans des bases de données relationnelles, constituant une source riche pour construire des réseaux sociaux. Le réseau, ainsi extrait, a souvent une taille importante ce qui rend son analyse et sa visualisation difficiles. Dans ce travail, nous proposons une étape d'extraction suivie d'une étape d'agrégation des réseaux sociaux à partir des bases de données relationnelles. L'étape d'extraction ou de construction transforme une base de données relationnelle en base de données graphe, puis le réseau social est extrait. L'étape d'agrégation, qui est basée sur l'algorithme k-SNAP, produit un graphe résumé.
J. Digit. Inf. Manag., 2008
The huge number of available documents on the Web makes finding relevant ones a challenge. Thus, ... more The huge number of available documents on the Web makes finding relevant ones a challenge. Thus, searching for information becomes more and more complex because of the growing volume of data and of its lack of structure. The quality of results that traditional full-text search engines provide is still not optimal for many types of user queries. Especially, the ambiguities of natural languages and abstract concepts are handled inadequately by full-text search engines. Ontologies provide a solution to these problems. They can help a user to find documents related to a specific domain. This paper proposes a new retrieval system based on ontologies. This system integrates results from traditional full-text engines, and thus supports a gradual transition from classical full-text search engines to ontology-based ones.
With the continual increase of the volume of availa ble information on the web, information acces... more With the continual increase of the volume of availa ble information on the web, information access and know ledge management become challenging. Thus, adding a seman tic dimension to the Web, by the deployment of ontologi es, contributes to solve many problems. In the context of the semantic Web, ontologies improve the exploitation of Web res ources by adding a consensual field of knowledge. The need fo r using domain ontology for information retrieval (IR) has been explored by some approaches to better answer users’ queries. However, ontology in IR system requires a regular updating, especially the addition of new concepts and relationships. In fact , IR systems are generally based on few number of domain ontology th at cannot be extended. This paper proposes an incremental approa ch for domain ontology learning. This approach is designed to be integrated into IR system based on ontology. It is ba ed on an ontological representation called "Metaontology." T he approach pr...
The present work introduces a set of solutions to extract graphs from enterprise data and facilit... more The present work introduces a set of solutions to extract graphs from enterprise data and facilitate the process of information search on these graphs. First of all we have defined a new graph model called the SPIDER-Graph, which models complex objects and permits to define heterogeneous graphs. Furthermore, we have developed a set of algorithms to extract the content of a database from an enterprise and to represent it in this new model. This latter representation allows us to discover relations that exist in the data but are hidden due to their poor compatibility with the classical relational model. Moreover, in order to unify the representation of all the data of the enterprise, we have developed a second approach which extracts from unstructured data an enterprise's ontology containing the most important concepts and relations that can be found in a given enterprise. Having extracted the graphs from the relational databases and documents using the enterprise ontology, we pro...
Conference en Recherche d'Infomations et Applications, 2008
MOTS-CLÉS : recherche d'information en ligne, construction d'ontologies ABSTRACT. The hug... more MOTS-CLÉS : recherche d'information en ligne, construction d'ontologies ABSTRACT. The huge number of available documents on the Web makes finding relevant ones challenging. Thus, searching for information becomes more and more complex because of the growing volume of data and of its lack of structure. The quality of results that traditional full-text search engines provide is still not optimal for
Http Www Theses Fr, Jun 22, 2012
Les cahiers du numérique, Sep 30, 2015
Le projet Campus AAR est un projet qui a comme objectif de constituer et exploiter des patrimoine... more Le projet Campus AAR est un projet qui a comme objectif de constituer et exploiter des patrimoines scientifiques des sciences humaines et sociales sous forme d’archives audiovisuelles numeriques. Ceci est mis en place a travers une plateforme logicielle appelee Studio Campus AAR qui permet a un detenteur d’archives d’analyser, exposer, republier, rechercher et rendre interoperables des ressources audiovisuelles. Dans cet article, l’environnement de publication de ce studio est presente. Le processus de publication est base sur des technologies du web semantique afin d’assister les auteurs a creer d’une maniere autonome leurs publications.
HAL (Le Centre pour la Communication Scientifique Directe), Dec 1, 2008
With the continual increase of the volume of available information on the web, information access... more With the continual increase of the volume of available information on the web, information access and knowledge management become challenging. Thus, adding a semantic dimension to the Web, by the deployment of ontologies, contributes to solve many problems. In the context of the semantic Web, ontologies improve the exploitation of Web resources by adding a consensual field of knowledge. The need for using domain ontology for information retrieval (IR) has been explored by some approaches to better answer users' queries. However, ontology in IR system requires a regular updating, especially the addition of new concepts and relationships. In fact, IR systems are generally based on few number of domain ontology that cannot be extended. This paper proposes an incremental approach for domain ontology learning. This approach is designed to be integrated into IR system based on ontology. It is based on an ontological representation called "Metaontology." The approach presented was tested and evaluated on a tourism ontology built from results of an online IR system based on ontology.
Lecture Notes in Computer Science, 2012
ABSTRACT In the enterprise context, people need to visualize different types of interactions betw... more ABSTRACT In the enterprise context, people need to visualize different types of interactions between heterogeneous objects in order to make the right decision. Therefore, we have proposed, in previous works, an approach of enterprise object graphs extraction which describes these interactions. One of the steps involved in this approach consists in identifying automatically the enterprise objects. Since the enterprise ontology has been used for describing enterprise objects and processes, we propose to integrate it in this process. The main contribution of this work is to propose an approach for enterprise ontology learning coping with both generic and specific aspects of enterprise information. It is three-folded: First, general enterprise ontology is semi-automatically built in order to represent general aspects. Second, ontology learning method is applied to enrich and populate this latter with specific aspects. Finally, the resulting ontology is used to identify objects in the graph extraction process.
HAL (Le Centre pour la Communication Scientifique Directe), Mar 12, 2008
La croissance très importante des informations disponibles sur Internet nécessite des outils de r... more La croissance très importante des informations disponibles sur Internet nécessite des outils de recherche de plus en plus performants permettant de discerner efficacement les informations intéressantes parmi des centaines voire des milliers de documents. Seulement, la qualité des résultats fournis par les moteurs de recherche traditionnels n'est pas toujours pertinente surtout quand il s' agit de composer plus d'une requête. Ceci est dû aux ambiguïtés linguistiques et aux concepts abstraits qui ne sont pas bien traités. L'utilisation ...
Lecture Notes in Computer Science, 2012
An adapted modeling and visualization technique of links and interactions between several objects... more An adapted modeling and visualization technique of links and interactions between several objects,e.g. customers and products, social network and etc,is a precious mean to permit a good understanding of a lot of situations in the enterprise's context. In this latter context, most of the time, these objects and their relations are stored in relational databases. But extracting and modeling heterogeneous graphs from databases are outside of the classical graph models possibilities, moreover when each node contains a set of values. On the other hand, graph models can be a natural way to present these graphs and facilitates their query. In this way, we propose a graph model named SPIDER-Graph which is adapted to represent interactions between complex heterogeneous objects extracted from a relational database. This model is used in our approach of heterogeneous object graph extraction from a relational database which is detailed in this paper.
In the enterprise context, an important amount of information is stored in relational databases. ... more In the enterprise context, an important amount of information is stored in relational databases. Therefore, relational database can be a rich source to extract social network. Moreover, it is not very suitable to present and store a social network. On the other hand, a graph database canmodel data in natural way and facilitates the query of data using graph operations.
The huge number of available documents on the Web makes finding relevant ones challenging. Thus, ... more The huge number of available documents on the Web makes finding relevant ones challenging. Thus, searching for information becomes more and more complex because of the growing volume of data and of its lack of structure. The quality of results that traditional full-text search engines provide is still not optimal for many types of user queries. Especially, the ambiguities of natural languages and abstract concepts are handled inadequately by full-text search engines. Ontologies provide a solution to these problems. They can help a user to find documents of a specific domain. This paper proposes a new retrieval system based on ontologies. This system integrates results from traditional full-text engines, and thus supports a gradual transition from classical full-text search engines to ontology-based ones.
The present work introduces a set of solutions to extract graphs from enterprise data and facilit... more The present work introduces a set of solutions to extract graphs from enterprise data and facilitate the process of information search on these graphs. First of all we have defined a new graph model called the SPIDER-Graph, which models complex objects and permits to define heterogeneous graphs. Furthermore, we have developed a set of algorithms to extract the content of a database from an enterprise and to represent it in this new model. This latter representation allows us to discover relations that exist in the data but are hidden due to their poor compatibility with the classical relational model. Moreover, in order to unify the representation of all the data of the enterprise, we have developed a second approach which extracts from unstructured data an enterprise's ontology containing the most important concepts and relations that can be found in a given enterprise. Having extracted the graphs from the relational databases and documents using the enterprise ontology, we pro...
With the continual increase of the volume of available information on the web, information access... more With the continual increase of the volume of available information on the web, information access and knowledge management become challenging. Thus, adding a semantic dimension to the Web, by the deployment of ontologies, contributes to solve many problems. In the context of the semantic Web, ontologies improve the exploitation of Web resources by adding a consensual field of knowledge. The need for using domain ontology for information retrieval (IR) has been explored by some approaches to better answer users ’ queries. However, ontology in IR system requires a regular updating, especially the addition of new concepts and relationships. In fact, IR systems are generally based on few number of domain ontology that cannot be extended. This paper proposes an incremental approach for domain ontology learning. This approach is designed to be integrated into IR system based on ontology. It is based on an ontological representation called "Metaontology. " The approach presented ...
Data manipulated in an enterprise context are structured data as well as unstructured data such a... more Data manipulated in an enterprise context are structured data as well as unstructured data such as emails, documents, social networks, etc. Graphs are a natural way of representing and modeling such data in a unified manner (Structured, semi-structured and unstructured ones). The main advantage of such a structure relies in the dynamic aspect and the capability to represent relations, even multiple ones, between objects. Recent database research work shows a growing interest in the definition of graph models and languages to allow a natural way of handling data appearing. In this chapter, we give a survey of the main graph database models and the associated graph query languages. We then present an application using a graph database to extract social networks. Graph Database For collaborative Communities............................................... 1
MOTS-CLES : recherche d'information en ligne, construction d'ontologies ABSTRACT. The hug... more MOTS-CLES : recherche d'information en ligne, construction d'ontologies ABSTRACT. The huge number of available documents on the Web makes finding relevant ones challenging. Thus, searching for information becomes more and more complex because of the growing volume of data and of its lack of structure. The quality of results that traditional full-text search engines provide is still not optimal for many types of user queries. The ambiguities of natural languages and abstract concepts are handled inadequately by full- text search engines. Ontologies provide a solution to these problems. An architecture composed of several ontologies is proposed to represent concepts as well as services of domain. In this paper, we expose the contribution of these ontologies in information retrieval and we propose a new retrieval system based on ontologies. Experimentation in the domain of the tourism is presented, and the gotten results are compared to other systems.
Lecture Notes in Social Networks, 2012
In the enterprise context, People need to visualize different types of interactions between heter... more In the enterprise context, People need to visualize different types of interactions between heterogeneous objects (e.g. product and site, customers and product, people interaction (social network)...). The existing approaches focus on social networks extraction using web document. However a considerable amount of information is stored in relational databases. Therefore, relational databases can be seen as rich sources for extracting a social network. The extracted network has in general a huge size which makes it difficult to analyze and visualize. An aggregation step is needed in order to have more understandable graphs. In this chapter, we propose a heterogeneous object graph extraction approach from a relational database and we present its application to extract social network. This step is followed by an aggregation step in order to improve the visualisation and the analyse of the extracted social network. Then, we aggregate the resulting network using the k-SNAP algorithm which produces a summarized graph.
Actes de la 5ème conférence en Recherche d'Information et Applications.(CORIA 2008), Mar 12, 2008
La croissance très importante des informations disponibles sur Internet nécessite des outils de r... more La croissance très importante des informations disponibles sur Internet nécessite des outils de recherche de plus en plus performants permettant de discerner efficacement les informations intéressantes parmi des centaines voire des milliers de documents. Seulement, la qualité des résultats fournis par les moteurs de recherche traditionnels n'est pas toujours pertinente surtout quand il s' agit de composer plus d'une requête. Ceci est dû aux ambiguïtés linguistiques et aux concepts abstraits qui ne sont pas bien traités. L'utilisation ...
Springer eBooks, 2011
Data manipulated in an enterprise context are structured data as well as unstructured data such a... more Data manipulated in an enterprise context are structured data as well as unstructured data such as emails, documents, social networks, etc. Graphs are a natural way of representing and modeling such data in a unified manner (Structured, semi-structured and unstructured ones). The main advantage of such a structure relies in the dynamic aspect and the capability to represent relations, even multiple ones, between objects. Recent database research work shows a growing interest in the definition of graph models and languages to allow a natural way of handling data appearing. In this chapter, we give a survey of the main graph database models and the associated graph query languages. We then present an application using a graph database to extract social networks.
Extraction et Gestion des Connaissances, 2011
Dans un contexte d'entreprise, beaucoup d'informations importantes restent stockées dans des base... more Dans un contexte d'entreprise, beaucoup d'informations importantes restent stockées dans des bases de données relationnelles, constituant une source riche pour construire des réseaux sociaux. Le réseau, ainsi extrait, a souvent une taille importante ce qui rend son analyse et sa visualisation difficiles. Dans ce travail, nous proposons une étape d'extraction suivie d'une étape d'agrégation des réseaux sociaux à partir des bases de données relationnelles. L'étape d'extraction ou de construction transforme une base de données relationnelle en base de données graphe, puis le réseau social est extrait. L'étape d'agrégation, qui est basée sur l'algorithme k-SNAP, produit un graphe résumé.
J. Digit. Inf. Manag., 2008
The huge number of available documents on the Web makes finding relevant ones a challenge. Thus, ... more The huge number of available documents on the Web makes finding relevant ones a challenge. Thus, searching for information becomes more and more complex because of the growing volume of data and of its lack of structure. The quality of results that traditional full-text search engines provide is still not optimal for many types of user queries. Especially, the ambiguities of natural languages and abstract concepts are handled inadequately by full-text search engines. Ontologies provide a solution to these problems. They can help a user to find documents related to a specific domain. This paper proposes a new retrieval system based on ontologies. This system integrates results from traditional full-text engines, and thus supports a gradual transition from classical full-text search engines to ontology-based ones.
With the continual increase of the volume of availa ble information on the web, information acces... more With the continual increase of the volume of availa ble information on the web, information access and know ledge management become challenging. Thus, adding a seman tic dimension to the Web, by the deployment of ontologi es, contributes to solve many problems. In the context of the semantic Web, ontologies improve the exploitation of Web res ources by adding a consensual field of knowledge. The need fo r using domain ontology for information retrieval (IR) has been explored by some approaches to better answer users’ queries. However, ontology in IR system requires a regular updating, especially the addition of new concepts and relationships. In fact , IR systems are generally based on few number of domain ontology th at cannot be extended. This paper proposes an incremental approa ch for domain ontology learning. This approach is designed to be integrated into IR system based on ontology. It is ba ed on an ontological representation called "Metaontology." T he approach pr...
The present work introduces a set of solutions to extract graphs from enterprise data and facilit... more The present work introduces a set of solutions to extract graphs from enterprise data and facilitate the process of information search on these graphs. First of all we have defined a new graph model called the SPIDER-Graph, which models complex objects and permits to define heterogeneous graphs. Furthermore, we have developed a set of algorithms to extract the content of a database from an enterprise and to represent it in this new model. This latter representation allows us to discover relations that exist in the data but are hidden due to their poor compatibility with the classical relational model. Moreover, in order to unify the representation of all the data of the enterprise, we have developed a second approach which extracts from unstructured data an enterprise's ontology containing the most important concepts and relations that can be found in a given enterprise. Having extracted the graphs from the relational databases and documents using the enterprise ontology, we pro...
Conference en Recherche d'Infomations et Applications, 2008
MOTS-CLÉS : recherche d'information en ligne, construction d'ontologies ABSTRACT. The hug... more MOTS-CLÉS : recherche d'information en ligne, construction d'ontologies ABSTRACT. The huge number of available documents on the Web makes finding relevant ones challenging. Thus, searching for information becomes more and more complex because of the growing volume of data and of its lack of structure. The quality of results that traditional full-text search engines provide is still not optimal for
Http Www Theses Fr, Jun 22, 2012