Catálogo de publicaciones - libros

is the term commonly used for the problem of answering queries on databases that violate certain integrity constraints. We address this problem for universal relations that are inconsistent with respect to a set of functional dependencies. In order to obtain more meaningful repairs, we apply a project-join dependency prior to repairing by tuple deletion. A positive result is that the additional project-join can yield tractability of consistent query answering.

Query processing performance in XML databases can be greatly enhanced by the usage of materialized views whose content has been stored in the database. This requires a method for identifying query subexpressions matching the views, a process known as view-based query rewriting. This process is quite complex for relational databases, and all the more daunting on XML databases.

Current XML materialized view proposals are based on tree patterns, since query navigation is conceptually close to such patterns. However, the existing algorithms for extracting tree patterns from XQuery do not detect patterns . Thus, complex, useful tree pattern views may be missed by the rewriting algorithm. We present a novel tree pattern extraction algorithm from XQuery queries, able to identify larger patterns than previous methods. Our algorithm has been implemented in an XML database prototype [5].

The MIEL++ system integrates data expressed in two different formalisms: a relational database and an XML database. The XML database is filled with data semi-automatically retrieved from the Web, which have been semantically enriched according to the ontology used in the relational database. These data may be imprecise and represented as possibility distributions. The MIEL++ querying system scans the two databases simultaneously in a transparent way for the end-user. To scan the XML database, the MIEL query is translated into an XML tree query. In this paper, we propose to introduce flexibility into the query processing of the XML database, in order to take into account the imperfections due to the semantic enrichment of its data. This flexibility relies on fuzzy queries and query rewriting which consists in generating a set of approximate queries from an original query using three transformation techniques: deletion, renaming and insertion of query nodes.

In this paper, we discuss an approach for relaxing a failing query in the context of flexible querying. The approach relies on the notion of proximity which is defined in a relative way. We show how such proximity allows for transforming a given predicate into an enlarged one. The resulting predicate is semantically not far from the original one and it is obtained by a simple fuzzy arithmetic operation. We show also how the search for a non-failing relaxed query over the lattice of relaxed queries can be improved by exploiting the notions of MFSs () and MGQs () of the original query.

We present a functional model for the analysis of large volumes of detailed transactional data, accumulated over time. In our model, the data schema is an acyclic graph with a single root, and data analysis queries are formulated using paths starting at the root. The root models the objects of an application and the remaining nodes model attributes of the objects. Our objective is to use this model as a simple interface for the analyst to formulate queries, and then map the queries to a commercially available system for the actual evaluation.

Recently, the spatial network databases (SNDB) have been studied for emerging applications such as location-based services including mobile search and car navigation. In practice, objects, like cars and people with mobile phones, can usually move on an underlying network (road, railway, sidewalk, river, etc.), where the network distance is determined by the length of the practical shortest path connecting two objects. In this paper, we propose materialization-based query processing algorithms for typical spatial queries in SNDB, such as range search and k nearest neighbors (k-NN) search. By using a materialization-based technique with the shortest network distances of all the nodes on the network, the proposed query processing algorithms can reduce the computation time of the network distance as well as the number of disk I/Os required for accessing nodes. Thus, the proposed query processing algorithms improve the existing efficient k-NN (INE) and range search (RNE) algorithms proposed by Papadias et al. [1], respectively. It is shown that our range query processing algorithm achieves about up to one of magnitude better performance than RNE and our k-NN query processing algorithm achieves about up to 150% performance improvements over INE.

Investments on multimedia technology enable us to store many more reflections of the real world in digital world as videos so that we carry a lot of information to the digital world directly. In order to store and efficiently query this information, a video database system (VDBS) is necessary. We propose a structural, event based and multimodal (SEBM) video data model which supports three different modalities that are visual, auditory and textual modalities for VDBSs and we can dissolve these three modalities within a single SEBM model. We answer the content-based, spatio-temporal and fuzzy queries of the user by using SEBM video data model more easily, since SEBM stores the video data as the way that user interprets the real world data. We follow divide and conquer technique when answering very complicated queries. We give the algorithms for querying on SEBM and try them on an implemented SEBM prototype system.

Given a query point , a () Query returns all points in the database having as their nearest neighbor. The problem of query has received much attention in a centralized database. However, not so much work has been done on this topic in the context of Peer-to-Peer (P2P) systems. In this paper, we shall do pioneering work on supporting distributed query in large distributed and dynamic P2P networks. Our proposed query algorithms are based on a distributed multi-dimensional index structure, called -tree, which is relying on a super-peer-based P2P overlay. The results of our performance evaluation with real spatial data sets show that our proposed algorithms are indeed practically feasible for answering distributed query in P2P systems.

The use of the Yager’s OWA operators within a flexible querying interface is discussed. The key issue is the adaptation of an OWA operator to the specifics of a user’s query. Some well-known approaches to the manipulation of the weights vector are reconsidered and a new one is proposed that is simple and efficient.

Time plays an important role in our everyday’s life. For a lot of observations we make and actions we perform, temporal information is relevant. The importance of time is reflected in the development of information systems such as (temporal) database systems and data warehouse systems, which have facilities to cope with temporal data and usually manage huge collections of historical data. It is a challenge to develop intuitive user interaction tools that allow users to fully explore these collections of temporal data. With this paper, we want to contribute to the development of such a tool. The presented approach is based on a visualization of time intervals as points in a two-dimensional space and on temporal reasoning based on this visualization. Flexibility is provided by allowing to cope with imperfections in both the modelling of time and the temporal reasoning.