The term quote semantic query optimization quote (SQO) denotes a methodology whereby queries against databases are optimized using semantic information about the database objects being queried. The result of semantically optimizing a query is another query which is syntactically different to the original, but semantically equivalent and which may be answered more efficiently than the original. SQO is distinctly different from the work performed by the conventional SQL optimizer. The SQL optimizer generates a set of logically equivalent alternative execution paths based ultimately on the rules of relational algebra. However, only a small proportion of the readily available semantic information is utilised by current SQL optimizers. Researchers in SQO agree that SQO can be very effective. However, after some twenty years of research into SQO, there is still no commercial implementation. In this thesis we argue that we need to quantify the conditions for which SQO is worthwhile. We investigate what these conditions are and apply this knowledge to relational database management systems (RDBMS) with static schemas and infrequently updated data. Any semantic query optimizer requires the ability to reason using the semantic information available, in order to draw conclusions which ultimately facilitate the recasting of the original query into a form which can be answered more efficiently. This reasoning engine is currently not part of any commercial RDBMS implementation. We show how a practical semantic query optimizer may be built utilising readily available semantic information, much of it already captured by meta-data typically stored in commercial RDBMS. We develop cost models which predict an upper bound to the amount of optimization one can expect when queries are pre-processed by a semantic optimizer. We present a series of empirical results to confirm the effectiveness or otherwise of various types of SQO and demonstrate the circumstances under which SQO can be effective.

No description available.

No description available.

As the number of the published web services increase, discovery of the web services with the desired functionality and quality is becoming a challenging process. Selecting the appropriate web services among the ones that oer the same functionality is also a challenging task. The web service repositories like UDDI (Universal Description Discovery and Integration) support only the syntactic searchs. Quality of service parameters for the published web services can not be queried over these repositories. We have proposed a query language that aims to overcome these problems. It enables its users to query the web services both syntactically and semantically. We also allow the users to specify the quality of service criteria which the desired web services should satisfy. We have developed a graphical query interface to assist the users in query sentence formulation process. The proposed work is developed as a submodule of the Domain Specific Web Service Discovery with Semantics (DSWSD-S) System. Aforementioned query language and the query interface are explained in detail in this thesis.

Dans le cadre d’une solution de modification de la requête, nous nous intéressons aux différentes façons d’utiliser la sémantique pour mieux exprimer le besoin d’information de l’utilisateur dans un contexte Web. Nous distinguons deux types de concepts : ceux identifiables dans une ressource sémantique comme une ontologie, et ceux que l’on extrait à partir d’un ensemble de documents de pseudo retour de pertinence. Nous proposons une Approche Sémantique Mixte d’Expansion et de Reformulation (ASMER) qui permet de modéliser l’utilisation de ces deux types de concepts dans une requête modifiée. Cette approche considère plusieurs défis liés à la modification automatique des requêtes, notamment le choix sélectif des termes d’expansion, le traitement des entités nommées et la reformulation de la requête finale.Bien que dans un contexte Web la précision soit le critère d’évaluation le plus adapté, nous avons aussi pris en compte le rappel pour étudier le comportement de notre approche sous plusieurs aspects. Ce choix a suscité une autre problématique liée à l’évaluation du rappel en recherche d’information. En constatant que les mesures précédentes ne répondent pas à nos contraintes, nous avons proposé la mesure MOR (Mesure Orientée Rappel), qui permet d’évaluer le rappel en tenant compte de la précision comme importante mais pas prioritaire dans un contexte dirigé rappel.En incluant MOR dans notre stratégie de test, nous avons évalué ASMER sur quatre collections Web issues des campagnes INEX et TREC. Nos expériences montrent qu’ASMER améliore la performance en précision par rapport aux requêtes originales et par rapport aux requêtes étendues par une méthode de l’état de l’art. / As a query expansion and reformulation solution, we are interested in the different ways the semantic could be used to translate users information need into a query. We define two types of concepts : those which we can identify in a semantic resource like an ontology, and the ones we extract from the collection of documents via pseudo relevance feedback procedure. We propose a semantic and mixed approach to query expansion and reformulation (ASMER) that allows to integrate these two types of concepts in an automatically modified query. Our approach considers many challenges, especially selective terms expansion, named entity treatment and query reformulation.Even though the precision is the evaluation criteria the most adapted to a web context, we also considered evaluating the recall to study the behavior of our model from different aspects. This choice led us to handle a different problem related to evaluating the recall in information retrieval. After realizing that actual measures don't satisfy our constraints, we proposed a new recall oriented measure (MOR) which considers the recall as a priority without ignoring the precision.Among other measures, MOR was considered to evaluate our approach ASMER on four web collection from the standard evaluation campaigns Inex and Trec. Our experiments showed that ASMER improves the precision of the non modified original queries. In most cases, our approach achieved statistically significant enhancements when compared to a state of the art query expansion method. In addition, ASMER retrieves the first relevant document in better ranks than the compared approaches, it also has slightly better recall according to the measure MOR.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2016-02-29T10:48:44Z No. of bitstreams: 2 Dissertação - Walquiria Fernandes Marins - 2015.pdf: 2611919 bytes, checksum: 3d20806ae28d0e0e4c891d8dd65cbd88 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-02-29T10:54:01Z (GMT) No. of bitstreams: 2 Dissertação - Walquiria Fernandes Marins - 2015.pdf: 2611919 bytes, checksum: 3d20806ae28d0e0e4c891d8dd65cbd88 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2016-02-29T10:54:01Z (GMT). No. of bitstreams: 2 Dissertação - Walquiria Fernandes Marins - 2015.pdf: 2611919 bytes, checksum: 3d20806ae28d0e0e4c891d8dd65cbd88 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2015-10-08 / There is an huge amount of data and information stored digitally. Part of this amount of data is available for consultation by Web, however, a significant portion is hidden, due to its storage form, and can’t be recovered by traditional search engines. This makes users face a common and growing challenge to search and find specific information. This challenge is enhanced by the unpreparedness of users to formulate searches and the limitations inherent in research technologies, that because of syntactic differences, can’t find probably relevant data. Aiming to expand the possibilities of semantic interpretation of a query, this work proposes an approach to interpretation of queries in natural language to relational databases through the use of domain ontologies as a tool for their interpretation and semantic enrichment. With the implementation of the approach and its appreciation against a backdrop of queries without the semantic enrichment it is observed that the approach contributes satisfactorily to identify the user’s intention. / Há uma quantidade enorme de dados e informações armazenadas digitalmente. Uma parte desse volume de dados está disponível para consultas através da Web, entretanto, uma parcela significativa está oculta, devido à sua forma de armazenamento, e não pode ser recuperada pelos mecanismos tradicionais de busca. Isso faz com que os usuários enfrentem um desafio comum e crescente para buscar e encontrar informações específicas. Este desafio é potencializado pelo despreparo dos usuários em formular buscas e pelas limitações inerentes às tecnologias de pesquisa que, em virtude de diferenças sintáticas, não conseguem encontrar dados provavelmente relevantes. Visando ampliar as possibilidades de interpretação semântica de uma consulta, este trabalho propõe uma abordagem de interpretação de consultas em linguagem natural a bancos de dados relacionais através do uso de ontologias de domínio como instrumento para sua interpretação e enriquecimento semântico. Com a implementação da abordagem e sua apreciação em relação a um cená- rio de consultas sem o enriquecimento semântico observa-se que a abordagem contribui satisfatoriamente para identificar a intenção do usuário.