Cheng, R., Xia, Y., Prabhakar, S., Shah, R., Vitter, J.: Efficient indexing methods for probabilistic threshold queries over uncertain data. In: VLDB, pp. 876-887 (2004). Digital Library. Google Scholar ... The importance of query processing over uncertain data has recently arisen due to its wide usage in many real-world …
An uncertain or probabilistic database is defined as a probability distribution over a set of deterministic database instances called possible worlds.. In the classical deterministic setting, the query processing problem is to compute the set of tuples representing the answer of a given query on a given database.
Recently, Yang et al [29] investigate the problem of range aggregate query processing over uncertain data in which two sampling approaches are proposed to estimate the aggregate values for the ...
We now introduce a probabilistic inverted index for USVA by extending the traditional inverted index [25], [57] for "exact" set-valued data. Fig. 1 shows the structure of the probabilistic inverted index. For each indexing item x ∈ G, the directory contains a pointer to an inverted list denoted as I(x).Each entry of I(x) is a pair (t·id, p), where t·id is …
Probabilistic Aggregate Queries on Uncertain Data Streams. Stream query processing, where data are naturally high-speed and unbounded, has attracted much attention. Similar to certain data streams, there are two models for processing uncertain data streams according to the time aspect: unbounded streaming model and …
Reverse nearest neighbor (RNN) search is very crucial in many real applications. In particular, given a database and a query object, an RNN query retrieves all the data objects in the database that have the query object as their nearest neighbors. Often, due to limitation of measurement devices, environmental disturbance, or …
Uncertain data streams are ubiquitous in many sensing and networking environments. Probabilistic aggregate query that returns a probability distribution to denote possible answers is extensively ...
To solve the above problems, edge computing has become a promising solution. In this paper, we propose a new algorithm for processing probabilistic skyline queries over uncertain data streams in an edge computing environment. We use the concept of a second skyline set to filter data that is unlikely to be the result of the skyline.
This report proposes a complete solution for the problem of evaluating ALL_SUM queries, based on a recursive approach, and implemented and conducted an extensive experimental evaluation over synthetic and real-world data sets; the results show its effectiveness. SUM queries are crucial for many applications that need to deal with …
This work extends the semantics of sliding window to define the novel concept of uncertain sliding windows and provides both exact and approximate algorithms for managing windows under existential uncertainty, and shows how current state-of-the-art techniques for answering similarity join queries can be easily adapted to be used with …
The importance of query processing over uncertain data has recently arisen due to its wide usage in many real-world applications. In the context of uncertain databases, previous work have studied many query types …
Correspond-ingly, we have to redefine the GNN query over uncertain objects. In particular, in an uncertain database, a probabilistic group nearest neighbor (PGNN) query …
Two pruning algorithms for efficiently processing PGNN query which are not sensitive to the shapes of uncertain regions are proposed, and outperform the existing work by about 2-3 times under various settings. Uncertain data are inherent in various applications, and group nearest neighbor (GNN) query is widely used in many fields. …
Large amount of uncertain data is collected by many emerging applications which contain multiple sources in a distributed manner. Previous efforts on querying uncertain data in distributed environment have only focus on ranking and skyline, join queries have not been addressed in earlier work despite their importance in databases.
Probabilistic Threshold Range Aggregate Query Processing over Uncertain Data Shuxiang Yang 1, Wenjie Zhang2, Ying Zhang,andXueminLin3 1 The University of New South Wales, Australia 2 The University of New South Wales / NICTA, Australia 3 Dalian Maritime University, China & UNSW / NICTA, Australia {syang, zhangw, yingz, …
Abstract. Large amount of uncertain data is inherent in many novel and important applications such as sensor data analysis and mobile data management. A probabilistic threshold range aggregate (PTRA) query retrieves summarized information about the uncertain objects satisfying a range query, with respect to a given probability …
Query processing over uncertain databases has played an increasingly important role in applications like multi-criteria decision making [32], data cleansing [29], and so on.One important query type in the uncertain database is called probabilistic ranked (PRank) query [25], which retrieves uncertain objects that are expected to have …
databases, we address join queries over uncertain data. We propose semantics for the join operation, define probabilistic operators over uncertain data, and propose join …
In this paper, we formalize two important query types: sliding-window probabilistic threshold sum query and sliding-window probabilistic threshold count …
Query Processing over Uncertain Data Nilesh Dalvi Troo.ly Inc. Dan Olteanu University of Oxford SYNONYMS Query Processing over Probabilistic Data DEFINITION An uncertain or probabilistic database is de ned as a probability distribution over a set of deterministic database instances called possible worlds.
Probabilistic Threshold Range Aggregate Query Processing over Uncertain Data (PDF) Probabilistic Threshold Range Aggregate Query Processing over Uncertain Data | wenjie zhang - Academia.edu Academia.edu no longer supports Internet Explorer.
There are various factors that cause the uncertainty, for instance randomness or incompleteness of data, limitations of equipment and delay or loss in data transfer. A probabilistic threshold range aggregate (PRTA) query retrieves summarized information about the uncertain objects in the database satisfying a range query, with respect to a ...
For decades, query processing over uncertain databases has received much attention from the database community due to the pervasive data uncertainty in many real-world applications such as ...
i in a continuous uncertain data model is represented as pdf(u i), and pdf(u i) = R x∈u i pdf(x)dx = 1. In our work, we consider uncertain data with the discrete probabilistic model and the discrete probabilistic data model can be defined as follows. Definition 1 (Discrete Probabilistic Data Model): Given an uncertain data object u
Probabilistic Threshold Range Aggregate Query Processing over Uncertain Data (PDF) Probabilistic Threshold Range Aggregate Query Processing over Uncertain Data | …
In this paper, we propose to express the similarity between two uncertain objects by probability density functions which assign a probability value to each possible distance value. By integrating these probabilistic distance functions directly into the join algorithms the full information provided by these functions is exploited.
A probabilistic threshold range aggregate (PTRA) query retrieves summarized information about the uncertain objects satisfying a range query, with respect to a given …
Uncertain data are inherent in various applications, and group nearest neighbor (GNN) query is widely used in many fields. Existing work for answering probabilistic GNN (PGNN) query on uncertain data are inefficient for …
A nearest neighbor (NN) query, which returns the most similar object to a user-specified query object, plays an important role in a wide range of applications and hence has received considerable attention. In many such applications, e.g., sensor data collection and location-based services, objects are inherently uncertain. Furthermore, …
The probabilistic threshold query (PTQ) is one of the most com-mon queries in uncertain databases, where all results satisfying the query with probabilities that meet the …
Evaluating probabilistic queries over imprecise data. In Proc. of the ACM SIGMOD Intl. Conf. on Management of Data, June 2003 ... uncertain query processing has become increasingly important, which dramatically differs from handling certain data in a traditional database. ... Probabilistic aggregate skyline join queries Proceedings of …
Uncertain data streams are ubiquitous in many sensing and networking environments. Probabilistic aggregate query that returns a probability distribution to denote possible answers is extensively used on such streams. In many monitoring applications, it is only necessary to know whether the result distribution exceeds user …
The probabilistic threshold query is one of the most common queries in uncertain databases, where a result satisfying the query must be also with probability meeting the threshold requirement. In this paper, we investigate probabilistic threshold keyword queries (PrTKQ)over XML data, which is not studied before. We first introduce …
