Uncertain databases have evolved as an active area of database research, surveyed, for example, in [10].The possible worlds semantics [1] is commonly used to deal with uncertain data. Several representation systems for uncertain databases have been proposed to provide efficient storage and query facilities for a potentially big number of possible worlds, see, e.g., [14,4,8]. Antova et al. intro...

In this paper, we show that there is a mismatch between information retrieval (IR) and database (DB) concepts, and we devise solutions for this problem. DB oriented approaches have to distinguish between the logical and the content structure of objects, and should also consider the layout structure. Data independence—not regarded in IR before—can be achieved by using the notion of vague predica...

This article proposes an approach to rely on the standard operators of relational algebra (including grouping and aggregation) for processing complex event without requiring window specifications. In this way the approach can process complex event queries of the kind encountered in applications such as emergency management in metro networks. This article presents Temporal Stream Algebra (TSA) w...

Probabilistic databases, which have been widely studied over the past years, lie at the expressive intersection of databases and probabilistic graphical models, thus aiming to provide efficient support for the evaluation of probabilistic queries over uncertain, relational data. Several Machine Learning approaches, on the one hand, have recently investigated the issue of distributed probabilisti...

Despite the vital role of information in relational-oriented firms, there are limited studies on the impact of information quality on relationship marketing. To address this gap, this study develops a conceptual model to examine the impact of information quality on the successful implementation of relationship marketing by assessing the mediating role of salespeople's relational competency. The...

This paper presents a novel approach to one-class-based uncertain data stream learning. Our proposed approach works in three steps. Firstly, we put forward a local kerneldensity-based method to generate a bound score for each instance, which refines the location of the corresponding instance. Secondly, we construct an uncertain one-class classifier by incorporating the generated bound score int...

Data Stream Management Systems (DSMS) have attracted much interest, and various extensions of relational-database query languages have been proposed for data streams. However, relational query languages were built on the solid bedrock of logic, while current DSMS languages and their computation models are missing such foundations. In this paper, we show that continuous queries can be characteri...

This paper proposes the integrated design of an event stream service system architecture (ESSSA) which can be used as a gateway to capture and process enormous amounts of event streams continuously generated by radio frequency identification (RFID) or variable sensors over ubiquitous sensor network (USN) installed in a wide variety of locations, transfer the refined events to the various event-...