Catálogo de publicaciones - libros

Locating the “right” piece of information among a wide range of available alternatives is not an easy task, as everyone has experienced at least once during his/her lifetime. In this paper we look at some recent issues arising when a database query is extended so as to include , which ultimately determine whether one alternative is reputed by the user better than another one. In particular, we focus on the case of queries, that strictly include well-known skyline queries, and describe how one can take advantage of the sorting machinery of standard database engines to speed-up evaluation both in centralized and distributed scenarios.

One of the most exciting accomplishments of computer science in the lifetime of this generation is the World Wide Web. The Web is a global electronic publishing medium. Its size has been growing with an enormous speed for over a decade. Most of its content is objectionable, but it also contains a huge amount of valuable information. The Web adds a new dimension to the concept of information explosion and tries to solve the very same problem by information retrieval systems known as Web search engines. We briefly review the information explosion problem and information retrieval systems, convey the past and state of the art in Turkish information retrieval research, illustrate some recent developments, and propose some future actions in this research area in Turkey.

The pedagogical concept of Project Organised Problem Based Learning (POPBL) has been implemented since 1974 at Aalborg University. With take-off in the experiences from this concept we have developed methodologies to integrate productive engineering and engineering education. We all know that the best way to learn and understand a theory is trying to see whether you can apply the theory. Engineering is problem solving – by applying results from engineering research. Therefore it is obvious to try to combine the fundamental learning process and engineering problem solving. Recently we have developed a methodology for continuing education integrated into the daily tasks called – mainly based on the same way of thinking. POPBL and FWBL as well as the link between these to methodologies will be presented in this paper.

L3S research focuses on three key enablers for the European Information Society, namely Knowledge, Information and Learning. The first part of the talk will review this project background context and highlight some of these projects in more detail.

The second part focuses on ”Personal Information Management” as guiding theme for several of these projects. Personal information management infrastructures provide advanced functionalities for accessing information from institutional repositories / digital libraries as well as personal collections, and facilitate knowledge sharing and exchange in work and learning contexts. Federated and peer-to-peer infrastructures, integrated search on metadata and full-text collections, and advanced personalization and ranking algorithms play an important role in this context.

Storing XML documents in relational database systems is still the most affordable and available storage solution. Meanwhile more work is still needed to provide efficient support for dynamic XML data stored in RDBMS. We present an abstract design for an Enabled XML Management System, and also propose a new labeling approach for nodes in XML documents, which we call XMask. XMask is a Dewey based labeling technique where each element is identified by a label consisting of two values (1) node Id (2) and node Mask. XMask can efficiently maintain the document structure and order with a short-length label that can fit in a 32-bit integer. We report the results of experimental evaluation using XML data between our approach and two other approaches, namely Edge and XRel, which use integer values for labeling as well. We show that our approach outperforms the other two approaches for complex queries.

The widespread use of XML brings out the need of ensuring the validity of XML data. The use of languages such as XML Schema makes easier the process of verification of XML documents, but the problem is that there are many constraints that can not be expressed by means of XML Schema. Besides, several works in the literature defend the consideration of a conceptual level in order to save XML designers from dealing with low level implementation issues. The approach of this paper is based on the inclusion of such a conceptual level, using UML as a conceptual modeling language. Starting from a UML class diagram annotated with conceptual constraints, our framework automatically generates an XML Schema together with a set of XSLT stylesheets to check those integrity constraints that can not be expressed in XML Schema.

Schema matching is a critical step in data integration from multiple heterogeneous data sources. This paper presents a new approach to schema matching, based on two observations. First, it is easier to find attribute correspondences between those schemas that are contextually similar. Second, the attribute correspondences found between these schemas can be used to help find new attribute correspondences between other schemas. Motivated by these observations, we propose a novel clustering-based approach to schema matching. First, we cluster schemas on the basis of their contextual similarity. Second, we cluster attributes of the schemas that are in the same schema cluster to find attribute correspondences between these schemas. Third, we cluster attributes across different schema clusters using statistical information gleaned from the existing attribute clusters to find attribute correspondences between more schemas. We leverage a fast clustering algorithm, the K-Means algorithm, to the above three clustering tasks. We have evaluated our approach in the context of integrating information from multiple web interfaces and the results show the effectiveness of our approach.

This paper studies -nearest-neighbor (NN) search on R-tree-based structures storing historical information about trajectories. We develop BFPNN, an efficient best-first based algorithm for handling NN search with arbitrary values of , which is I/O optimal, i.e., it performs a single access only to those qualifying nodes that may contain the final result. Furthermore, in order to save memory space consumption and reduce CPU overhead further, several effective pruning heuristics are also proposed. Finally, extensive experiments with synthetic and real datasets show that BFPNN outperforms its competitor significantly in both efficiency and scalability in all cases.

We propose a new architecture for object database access and management. It is based on updateable views which provide universal mappings of stored objects onto virtual ones. The mechanism preserves full transparency of virtual objects either for retrieval and any kind of updating. It provides foundation for three-level database architecture and correspondingly three database development roles: (1) a database programmer defines stored objects, i.e. their state and behavior; (2) a database administrator (DBA) creates views and interfaces which encapsulate stored objects and possibly limit access rights on them; (3) an application programmer or a user receives access and updating grants from DBA in the form of interfaces to views. We present a concrete solution that we are developing as a platform for grid and Web applications. The solution is supported by an intuitive methodology of schema development, determining the perspectives and responsibilities of each participant role.

Spatial information processing is an active research field in database technology. Spatial databases store information about the position of individual objects in space [6]. Our current research is focused on providing an efficient caching structure for a telemetric data warehouse. We perform spatial objects clustering when creating levels of the structure. For this purpose we employ a density-based clustering algorithm. The algorithm requires an user-defined parameter . As we cannot get the from user for every level of the structure we propose a heuristic approach for calculating the parameter. Automatic Calculation (AEC) algorithm analyzes pairs of points defining two quantities: distance between the points and density of the stripe between the points. In this paper we describe in detail the algorithm operation and interpretation of the results. The AEC algorithm was implemented in one centralized and two distributed versions. Included test results present the algorithm correctness and efficiency against various datasets.