Ranked Relations: Query Languages and Query Processing Methods for Multimedia

2004 ◽  
Vol 24 (3) ◽  
pp. 197-214 ◽  
Author(s):  
Sibel Adali ◽  
Corey Bufi ◽  
Maria-Luisa Sapino
Keyword(s):  
Query Processing ◽  
Query Languages ◽  
Processing Methods

DocBase

2013 ◽  
pp. 365-393
Author(s):  
Arijit Sengupta ◽  
Ramesh Venkataraman
Keyword(s):  
Query Processing ◽  
Query Language ◽  
Formal Model ◽  
Query Languages ◽  
Prototype System ◽  
Storage And Retrieval ◽  
Visual Query Formulation ◽  
Visual Query ◽  
Nested Relations ◽  
Entity Relationship

This chapter introduces a complete storage and retrieval architecture for a database environment for XML documents. DocBase, a prototype system based on this architecture, uses a flexible storage and indexing technique to allow highly expressive queries without the necessity of mapping documents to other database formats. DocBase is an integration of several techniques that include (i) a formal model called Heterogeneous Nested Relations (HNR), (ii) a conceptual model XER (Extensible Entity Relationship), (ii) formal query languages (Document Algebra and Calculus), (iii) a practical query language (Document SQL or DSQL), (iv) a visual query formulation method with QBT (Query By Templates), and (v) the DocBase query processing architecture. This paper focuses on the overall architecture of DocBase including implementation details, describes the details of the query-processing framework, and presents results from various performance tests. The paper summarizes experimental and usability analyses to demonstrate its feasibility as a general architecture for native as well as embedded document manipulation methods.

scholarly journals A Method for Processing Top-k Continuous Query on Uncertain Data Stream in Sliding Window Model

2021 ◽  
Vol 16 ◽  
pp. 261-269
Author(s):  
Raja Azhan Syah Raja Wahab ◽  
Siti Nurulain Mohd Rum ◽  
Hamidah Ibrahim ◽  
Fatimah Sidi ◽  
Iskandar Ishak
Keyword(s):  
Query Processing ◽  
Data Streams ◽  
Data Stream ◽  
Uncertain Data ◽  
Research Work ◽  
Computational Cost ◽  
Sliding Window ◽  
Possible World ◽  
Processing Methods ◽  
Uncertain Data Streams

The data stream is a series of data generated at sequential time from different sources. Processing such data is very important in many contemporary applications such as sensor networks, RFID technology, mobile computing and many more. The huge amount data generated and frequent changes in a short time makes the conventional processing methods insufficient. The Sliding Window Model (SWM) was introduced by Datar et. al to handle this problem. Avoiding multiple scans of the whole data sets, optimizing memory usage, and processing only the most recent tuple are the main challenges. The number of possible world instances grows exponentially in uncertain data and it is highly difficult to comprehend what it takes to meet Top-k query processing in the shortest amount of time. Following the generation of rules and the probability theory of this model, a framework was anticipated to sustain top-k processing algorithm over the SWM approach until the candidates expired. Based on the literature review study, none of the existing work have been made to tackle the issue arises from the top-k query processing of the possible world instance of the uncertain data streams within the SWM. The major issue resulted from these scenarios need to be addressed especially in the computation redundancy area that contributed to the increases of computational cost within the SWM. Therefore, the main objective of this research work is to propose the top-k query processing methods over uncertain data streams in SWM utilizing the score and the Possible World (PW) setting. In this study, a novel expiration and object indexing method is introduced to address the computational redundancy issues. We believed the proposed method can reduce computational costs and by managing insertion and exit policy on the right tuple candidates within a specified window frame. This research work will contribute to the area of computational query processing.

scholarly journals Query Processing of Geosocial Data in Location-Based Social Networks

2021 ◽  
Vol 11 (1) ◽  
pp. 19
Author(s):  
Arianna D’Ulizia ◽  
Patrizia Grifoni ◽  
Fernando Ferri
Keyword(s):  
Query Processing ◽  
Future Perspectives ◽  
Access Method ◽  
Processing Methods ◽  
Data Representations ◽  
The Common ◽  
Use Of Social Media ◽  
Location Based Social Networks ◽  
Evaluation Approaches ◽  
Near Future

The increasing use of social media and the recent advances in geo-positioning technologies have produced a great amount of geosocial data, consisting of spatial, textual, and social information, to be managed and queried. In this paper, we focus on the issue of query processing by providing a systematic literature review of geosocial data representations, query processing methods, and evaluation approaches published over the last two decades (2000–2020). The result of our analysis shows the categories of geosocial queries proposed by the surveyed studies, the query primitives and the kind of access method used to retrieve the result of the queries, the common evaluation metrics and datasets used to evaluate the performance of the query processing methods, and the main open challenges that should be faced in the near future. Due to the ongoing interest in this research topic, the results of this survey are valuable to many researchers and practitioners by gaining an in-depth understanding of the geosocial querying process and its applications and possible future perspectives.

Intelligent Querying Techniques for Sensor Data Fusion

2010 ◽  
pp. 213-233 ◽  
Author(s):  
Shi-Kuo Chang ◽  
Gennaro Costagliola ◽  
Erland Jungert ◽  
Karin Camara
Keyword(s):  
Data Fusion ◽  
Query Processing ◽  
Query Language ◽  
Query Languages ◽  
Multimedia Data ◽  
Sensor Data ◽  
Multiple Sources ◽  
Sensor Data Fusion ◽  
Temporal Query Language ◽  
Processing Techniques

Sensor data fusion imposes a number of novel requirements on query languages and query processing techniques. A spatial/temporal query language called SQL has been proposed to support the retrieval of multimedia information from multiple sources and databases. This chapter investigates intelligent querying techniques including fusion techniques, multimedia data transformations, interactive progressive query building and SQL query processing techniques using sensor data fusion. The authors illustrate and discuss tasks and query patterns for information fusion, provide a number of examples of iterative queries and show the effectiveness of SQL in a command-action scenario.

Extending query languages for in-network query processing

2011 ◽  
Author(s):  
George Valkanas ◽  
Dimitrios Gunopulos ◽  
Ixent Galpin ◽  
Alasdair J. G. Gray ◽  
Alvaro A. A. Fernandes
Keyword(s):  
Query Processing ◽  
Query Languages

scholarly journals Fuzzy Query Languages for Multimedia Data

2011 ◽  
pp. 201-212 ◽  
Author(s):  
Paolo Ciaccia ◽  
Wilma Penzo ◽  
Danilo Montesi ◽  
Alberto Trombetta
Keyword(s):  
Query Processing ◽  
Query Languages ◽  
User Preferences ◽  
Multimedia Data ◽  
Fuzzy Query ◽  
Data User ◽  
Similarity Query ◽  
Common Framework ◽  
Logical Connectives ◽  
Algebraic Operators

This chapter presents a fuzzy-based algebra, called SAMEW, to query multimedia objects. SAMEW allows for dealing within a common framework with several aspects relevant to similarity query processing as well as with the inherent imprecision that characterizes data, user requests and query results. Non-Boolean, namely fuzzy and similarity, predicates are used to rank tuples according to specific criteria. Complex multi-predicate queries can be formed by means of logical connectives, whose semantics is parameterized in order to adapt to specific scenarios. The same holds for the semantics of algebraic operators. These include properly extended traditional relational operators and new operators which allow threshold and best-matches queries to be easily expressed. A further important feature of SAMEW is the possibility of weighting both predicates and operands of algebraic operators so as to better fit user preferences/requirements. A working example dealing with Web data is used throughout the chapter to show the potentialities of SAMEW. Optimization issues are also briefly discussed.

scholarly journals Performance and scalability of indexed subgraph query processing methods

2015 ◽  
Vol 8 (12) ◽  
pp. 1566-1577 ◽  
Author(s):  
Foteini Katsarou ◽  
Nikos Ntarmos ◽  
Peter Triantafillou
Keyword(s):  
Query Processing ◽  
Processing Methods ◽  
Subgraph Query

Verification of Super-Peer Model for Query Processing in Peer-to-Peer Networks

2016 ◽  
pp. 306-332
Author(s):  
J. Pourqasem ◽  
S.A. Edalatpanah
Keyword(s):  
Distributed Systems ◽  
Query Processing ◽  
Large Scale ◽  
Peer To Peer ◽  
P2p Networks ◽  
Processing Methods ◽  
Super Node ◽  
And Performance ◽  
Processing Techniques ◽  
Super Peer

Equal peers in peer-to-peer (P2P) networks are the drawbacks of system in term of bandwidth, scalability and efficiency. The super-peer model is based on heterogeneity and different characteristics of peers in P2P networks. The P2P networks and large- scale distributed systems based on P2P networks use the super-peer model to design the query processing mechanism. This chapter first reviews the query processing methods in P2P networks, in which the authors classify theses query processing approaches in Unstructured and Structured mechanisms. Furthermore, the query processing techniques in distributed systems based on P2P networks are discussed. Afterward, authors concentrate on super-peer model to process the query of peers in P2P networks. Authors present the query processing methods in P2P-based distributed systems using the super node. Finally, the chapter provides some examples of each of the presented query processing techniques, and then illustrates the properties of each of them in terms of scalability and performance issues.

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