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In the real world, various systems can be modeled using heterogeneous networks which consist of entities of different types. Many problems on such networks can be mapped to an underlying critical problem of discovering top-K subgraphs of entities with rare and surprising associations. Answering such subgraph queries efficiently involves two main challenges: (1) computing all matching subgraphs which...
A digital data collection (e.g., scientific publications, enterprise reports, news, and social media) can often be modeled as a heterogeneous information network, linking text with multiple types of entities. Constructing high-quality concept hierarchies that can represent topics at multiple granularities benefits tasks such as search, information browsing, and pattern mining. In this work we present...
A Cyber-Physical System (CPS) integrates physical devices (e.g., sensors, cameras) with cyber (or informational) components to form a situation-integrated analytical system that may respond intelligently to dynamic changes of the real-world situations. CPS claims many promising applications, such as traffic observation, battlefield surveillance and sensor-network based monitoring. One important research...
Searching and mining large graphs today is critical to a variety of application domains, ranging from personalized recommendation in social networks, to searches for functional associations in biological pathways. In these domains, there is a need to perform aggregation operations on large-scale networks. Unfortunately the existing implementation of aggregation operations on relational databases does...
Since Jim Gray introduced the concept of rdquodata cuberdquo in 1997, data cube, associated with online analytical processing (OLAP), has become a driving engine in data warehouse industry. Because the boom of Internet has given rise to an ever increasing amount of text data associated with other multidimensional information, it is natural to propose a data cube model that integrates the power of...
Ranking has been popularly used for intelligent data retrieval in both database and machine learning communities. Recently, there were studies on integrating these two approaches to support soft queries, based on a user's sense of relevance and preference, for ranking with numerical attributes. However, in real life, it is desirable to use categorical attributes together with numerical ones in ranking...
Many new applications that involve decision making need online (i.e., OLAP-styled) preference analysis with multidimensional Boolean selections. Typical preference queries includes top-k queries and skyline queries. An analytical query often comes with a set of Boolean predicates that constrain a target subset of data, which, may also vary incrementally by drilling/rolling operators. To efficiently...
Recent studies on efficiently answering subspace skyline queries can be separated into two approaches. The first focused on pre-materializing a set of skylines points in various subspaces while the second focus on dynamically answering the queries by using a set of anchors to prune off skyline points through spatial reasoning. Despite effort to compress the pre-materialized subspace skylines through...
Most of the existing work on skyline query has been extensively used in decision support, recommending systems etc, and mainly focuses on the efficiency issue for a single table. However the data retrieved by users for the targeting skylines may often be stored in multiple tables, thus require to perform join operations among tables. As a result, the cost on computing skylines on the joined table...
A deductive and object-oriented spatial (DOOS) database system enhances a spatial database system with deductive and object-oriented features. Two major kinds of computations co-exist in a DOOS database system: (1) spatial reasoning based on spatial relationships specified by spatial (deduction) rules, and (2) spatial computation based on computationally intensive geometric algorithms (methods)....
The processing of recursive queries in relational database systems poses a great challenge in research on expert database systems. This paper uses both analytical and experimental methods to investigate the performance of several different algorithms in processing a recursive query in first-order recursive databases. The analytical method estimated the I/O and CPU cost and the storage needed in processing...
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