Efficient Social Network Data Query Processing On Mapreduce
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| Author | : Liu Liu |
| Publisher | : |
| Total Pages | : 59 |
| Release | : 2013 |
| Genre | : Cloud computing |
| ISBN | : |
Social network data analysis becomes increasingly important today. In order to improve the integration and reuse of their data, many social networks start to apply RDF to present the data. Accordingly, one common approach for social network data analysis is to employ SPARQL to query RDF data. As the sizes of social networks expand rapidly, queries need to be executed in parallel such as using the MapReduce framework. However, the state-of-the-art translation from SPARQL queries to MapReduce jobs mainly follows a two layer rule, in which SPARQL is first translated to SQL join, is not efficient. In this thesis, we introduce two primitives to enable automatic translation from SPARQL to MapReduce, and to enable efficient execution of the SPARQL queries. We use multiple-join-with-filter to substitute traditional SQL multiple join when feasible, and merge different stages in the MapReduce query workflow. The evaluation on social network benchmarks shows that these two primitives can achieve up to 2x speedup in query running time compared with the original two layer scheme.
| Author | : Ahmed Al-Baghdadi |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2022 |
| Genre | : |
| ISBN | : |
Recently, location-based social networks, that involve both social and spatial information, have received much attention in many real-world applications such as location-based services (LBS), map utilities, business planning, and so on. User's location is one of the most important components of user context that implies extensive knowledge about an individual's interests and behavior, thereby providing researchers with opportunities to better understand users in a social structure according to not only online user behavior but also the user mobility and activities in the physical world. In this dissertation, we have an initial study of query processing over spatial-social networks and propose suitable solutions of query processing over spatial-social networks by proposing new novel queries that are Community Search (CS), Group Planning (GP), and Community Detection (CD) over the spatial-social network settings. For each proposed query over spatial-social networks, we have designed effective pruning strategies to reduce the search space by filtering false alarms, proposed effective indexing mechanisms to facilitate the query processing, and develop efficient query answering algorithms via index traversals. Extensive experiments have been conducted to evaluate the efficiency and effectiveness of our proposed queries processing approaches.
| Author | : Abdelkader Hameurlain |
| Publisher | : Springer |
| Total Pages | : 194 |
| Release | : 2016-02-19 |
| Genre | : Computers |
| ISBN | : 3662495341 |
This, the 25th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five fully revised selected papers focusing on data and knowledge management systems. Topics covered include a framework consisting of two heuristics with slightly different characteristics to compute the action rating of data stores, a theoretical and experimental study of filter-based equijoins in a MapReduce environment, a constraint programming approach based on constraint reasoning to study the view selection and data placement problem given a limited amount of resources, a formalization and an approximate algorithm to tackle the problem of source selection and query decomposition in federations of SPARQL endpoints, and a matcher factory enabling the generation of a dedicated schema matcher for a given schema matching scenario.
| Author | : My T. Thai |
| Publisher | : CRC Press |
| Total Pages | : 335 |
| Release | : 2016-12-01 |
| Genre | : Business & Economics |
| ISBN | : 1315396688 |
This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.
| Author | : Jimmy Lin |
| Publisher | : Springer Nature |
| Total Pages | : 171 |
| Release | : 2022-05-31 |
| Genre | : Computers |
| ISBN | : 3031021363 |
Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well. Table of Contents: Introduction / MapReduce Basics / MapReduce Algorithm Design / Inverted Indexing for Text Retrieval / Graph Algorithms / EM Algorithms for Text Processing / Closing Remarks
| Author | : Gabor Szabo |
| Publisher | : John Wiley & Sons |
| Total Pages | : 356 |
| Release | : 2018-09-18 |
| Genre | : Computers |
| ISBN | : 1118824903 |
Harness the power of social media to predict customer behavior and improve sales Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses. Social Media Data Mining and Analytics isn't just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media - examples include Twitter, Wikipedia, Stack Exchange, LiveJournal, movie reviews, and other rich data sources. In it, you will learn: The four key characteristics of online services-users, social networks, actions, and content The full data discovery lifecycle-data extraction, storage, analysis, and visualization How to work with code and extract data to create solutions How to use Big Data to make accurate customer predictions How to personalize the social media experience using machine learning Using the techniques the authors detail will provide organizations the competitive advantage they need to harness the rich data available from social media platforms.
| Author | : Wenguang Chen |
| Publisher | : Springer |
| Total Pages | : 335 |
| Release | : 2016-02-02 |
| Genre | : Computers |
| ISBN | : 9811004579 |
This book constitutes the refereed proceedings of the First National Conference on Big Data Technology and Applications, BDTA 2015, held in Harbin, China, in December 2015. The 26 revised papers presented were carefully reviewed and selected from numerous submissions. The papers address issues such as the storage technology of Big Data; analysis of Big Data and data mining; visualization of Big Data; the parallel computing framework under Big Data; the architecture and basic theory of Big Data; collection and preprocessing of Big Data; innovative applications in some areas, such as internet of things and cloud computing.
| Author | : Bhavani Thuraisingham |
| Publisher | : CRC Press |
| Total Pages | : 586 |
| Release | : 2016-04-06 |
| Genre | : Computers |
| ISBN | : 1482243288 |
Analyzing and Securing Social Networks focuses on the two major technologies that have been developed for online social networks (OSNs): (i) data mining technologies for analyzing these networks and extracting useful information such as location, demographics, and sentiments of the participants of the network, and (ii) security and privacy technolo
| Author | : Abdelkader Hameurlain |
| Publisher | : Springer Nature |
| Total Pages | : 247 |
| Release | : 2021-01-16 |
| Genre | : Computers |
| ISBN | : 3662629194 |
The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 47th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, constitutes a special issue focusing on Digital Ecosystems and Social Networks. The 9 revised selected papers cover topics that include Social Big Data, Data Analysis, Cloud-Based Feedback, Experience Ecosystems, Pervasive Environments, and Smart Systems.
| Author | : Mārīte Kirikova |
| Publisher | : Springer |
| Total Pages | : 426 |
| Release | : 2017-09-15 |
| Genre | : Computers |
| ISBN | : 3319669176 |
This book constitutes the proceedings of the 21st European Conference on Advances in Databases and Information Systems, ADBIS 2017, held in Nicosia, Cyprus, in September 2017. The 26 regular papers presented together with one keynote paper and one keynote abstract were carefully selected and reviewed from numerous submissions. The papers are organized in topical sections such as conceptual modeling and human factors; subsequence matching and streaming data; OLAP; graph databases; spatial data management; parallel and distributed data processing; query optimization, recovery, and databases on modern hardware; semantic data processing; and additional database and information systems topics.
