SIGMOD

Association-rule mining has proved a highly successful technique for extracting useful information from very large databases. This success is attributed not only to the appropriateness of the objectives, but to the fact that a number of new query-...

From the standpoint of supporting human-centered discovery of knowledge, the present-day model of mining association rules suffers from the following serious shortcomings: (i) lack of user exploration and control, (ii) lack of focus, and (iii) rigid ...

Association rule mining recently attracted strong attention. Usually, the classification hierarchy over the data items is available. Users are interested in generalized association rules that span different levels of the hierarchy, since sometimes more ...

Correlated queries are very common and important in decision support systems. Traditional nested iteration evaluation methods for such queries can be very time consuming. When they apply, query rewriting techniques have been shown to be much more ...

There is already a sizable body of proposals on OODB query optimization. One of the most challenging problems in this area is query unnesting, where the embedded query can take any form, including aggregation and universal quantification. Although there ...

Rule-based optimizers are extensible because they consist of modifiable sets of rules. For modification to be straightforward, rules must be easily reasoned about (i.e., understood and verified). At the same time, rules must be expressive and efficient (...

Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clusters with spherical shapes and similar sizes, or are very fragile in the ...

We present a pattern-mining algorithm that scales roughly linearly in the number of maximal patterns embedded in a database irrespective of the length of the longest pattern. In comparison, previous algorithms based on Apriori scale exponentially with ...

Data mining applications place special requirements on clustering algorithms including: the ability to find clusters embedded in subspaces of high dimensional data, scalability, end-user comprehensibility of the results, non-presumption of any canonical ...

For a number of reasons, even the best query optimizers can very often produce sub-optimal query execution plans, leading to a significant degradation of performance. This is especially true in databases used for complex decision support queries and/or ...

The proliferation of the World Wide Web has brought information retrieval (IR) techniques to the forefront of search technology. To the average computer user, “searching” now means using IR-based systems for finding information on the WWW or in other ...

Remote data access from disparate sources across a wide-area network such as the Internet is problematic due to the unpredictable nature of the communications medium and the lack of knowledge about the load and potential delays at remote sites. ...

In this paper, we propose the Pyramid-Technique, a new indexing method for high-dimensional data spaces. The Pyramid-Technique is highly adapted to range query processing using the maximum metric L_max. In contrast to all other index structures, the ...

For an increasing number of modern database applications, efficient support of similarity search becomes an important task. Along with the complexity of the objects such as images, molecules and mechanical parts, also the complexity of the similarity ...

Databases are increasingly being used to store multi-media objects such as maps, images, audio and video. Storage and retrieval of these objects is accomplished using multi-dimensional index structures such as R*-trees and SS-trees. As dimensionality ...

Due to the development of the World Wide Web, the integration of heterogeneous data sources has become a major concern of the database community. Appropriate architectures and query languages have been proposed. Yet, the problem of data conversion which ...

Schematic heterogeneity arises when information that is represented as data under one schema, is represented within the schema (as metadata) in another. Schematic heterogeneity is an important class of heterogeneity that arises frequently in integrating ...

Most databases contain “name constants” like course numbers, personal names, and place names that correspond to entities in the real world. Previous work in integration of heterogeneous databases has assumed that local name constants can be mapped into ...

This paper presents DEDALE, a spatial database system intended to overcome some limitations of current systems by providing an abstract and non-specialized data model and query language for the representation and manipulation of spatial objects. DEDALE ...

Similarity queries are fundamental operations that are used extensively in many modern applications, whereas disk arrays are powerful storage media of increasing importance. The basic trade-off in similarity query processing in such a system is that ...

Two new spatial join operations, distance join and distance semi-join, are introduced where the join output is ordered by the distance between the spatial attribute values of the joined tuples. Incremental algorithms are presented for computing these ...

The Relational On-Line Analytical Processing (ROLAP) is emerging as the dominant approach in data warehousing with decision support applications. In order to enhance query performance, the ROLAP approach relies on selecting and materializing in summary ...

Caching has been proposed (and implemented) by OLAP systems in order to reduce response times for multidimensional queries. Previous work on such caching has considered table level caching and query level caching. Table level caching is more suitable ...

Database researchers have made significant progress on several research issues related to multidimensional data analysis, including the development of fast cubing algorithms, efficient schemes for creating and maintaining precomputed group-bys, and the ...

Often interesting structured or semistructured data is not in database systems but in HTML pages, text files, or on paper. The data in these formats is not usable by standard query processing engines and hence users need a way of extracting data from ...

Semistructured data is characterized by the lack of any fixed and rigid schema, although typically the data has some implicit structure. While the lack of fixed schema makes extracting semistructured data fairly easy and an attractive goal, presenting ...

A major challenge in indexing unstructured hypertext databases is to automatically extract meta-data that enables structured search using topic taxonomies, circumvents keyword ambiguity, and improves the quality of search and profile-based routing and ...

Next generation decision support applications, besides being capable of processing huge amounts of data, require the ability to integrate and reason over data from multiple, heterogeneous data sources. Often, these data sources differ in a variety of ...

In large data recording and warehousing environments, it is often advantageous to provide fast, approximate answers to queries, whenever possible. Before DBMSs providing highly-accurate approximate answers can become a reality, many new techniques for ...

Data mining on large data warehouses is becoming increasingly important. In support of this trend, we consider a spectrum of architectural alternatives for coupling mining with database systems. These alternatives include: loose-coupling through a SQL ...