Massive Data Analysis: Tasks, Tools, Applications, and Challenges

Pusala, Murali; Salehi, Mohsen Amini; Katukuri, Jayasimha; Xie, Ying; Raghavan, Vijay V.

doi:10.1007/978-81-322-3628-3_2

Cited by 14 publications

(11 citation statements)

References 28 publications

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“…Thus, it is an opportunity for designers to enhance the learning process by tracking and monitoring new feeds from a variety of channels. On the other hand, it would be possible to use simple techniques such as drawing graphs to discover patterns in the data, use regression to understand the correlation between different variables, or visualise it to understand the data better (Pusala et al, 2016). Processing different types of data and their correlation is critical to the process, as it may help us in discovering new relationships and patterns in the data.…”

Section: Analysis Based On Datamentioning

confidence: 99%

Creativity Forward: A Framework That Integrates Data Analysis Techniques to Foster Creativity Within the Creative Process in User Experience Contexts

Gómez

2021

Creativity Studies

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The latest technological advancements allow users to generate a large volume of data related to their experiences and needs. However, the absence of an advanced methodology that links the big data and the creative process prevents the effective use of the data and extracting all its potential and knowledge in this context, which is crucial in offering user-centred solutions. Incorporating data creatively and critically as design material can help us learn and understand user needs better. Therefore, design can bring deeper meaning to data, just as data can enhance design practice. Accordingly, this work raises a reflection on whether designers could appropriate the workflow of data science in order to integrate it into the research process in the creative process within a framework of user experience analysis. The proposed model: data-driven design model, enhances the exploratory design of problem space and assists in the creation of ideas during the conceptual design phase. In this way, this work offers an integrated vision, enhancing creativity in industrial design as an instrument for the achievement of the proper and necessary balance between intuition and reason, design, and science.

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Section: Analysis Based On Datamentioning

confidence: 99%

Creativity Forward: A Framework That Integrates Data Analysis Techniques to Foster Creativity Within the Creative Process in User Experience Contexts

Gómez

2021

Creativity Studies

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“…The arrangement just described is in fact an example of a column-based layout. File Semantics is a a single-column file whereas the file Points, comprising a total of four columns, is an example of a column-family [65] as it groups the fundamental LiDAR information into a single entity. For convenience, we refer to the aforementioned two-file arrangement as the Semantic3D format.…”

Section: Semantic3d: a Simple Semantic Point Cloud Schemementioning

confidence: 99%

A Simple Semantic-Based Data Storage Layout for Querying Point Clouds

El-Mahgary

Virtanen

Hyyppä

2020

IJGI

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The importance of being able to separate the semantics from the actual (X,Y,Z) coordinates in a point cloud has been actively brought up in recent research. However, there is still no widely used or accepted data layout paradigm on how to efficiently store and manage such semantic point cloud data. In this paper, we present a simple data layout that makes use the semantics and that allows for quick queries. The underlying idea is especially suited for a programming approach (e.g., queries programmed via Python) but we also present an even simpler implementation of the underlying technique on a well known relational database management system (RDBMS), namely, PostgreSQL. The obtained query results suggest that the presented approach can be successfully used to handle point and range queries on large points clouds.

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“…Searchable encryption solutions providing keyword or regular expression-based search abilities are useful when users exactly know what keywords they are searching for in the documents. However, with a growing collection of documents and the emergence of big data, 52,53 the data users may not remember the exact keywords they want to retrieve, or they might want to search for documents that are more broadly related to a topic. 28,34 For instance, in a hospital with encrypted medical records, a doctor may desire to search for records using the query ''heart disease.''…”

Section: Semantic Searchmentioning

confidence: 99%

Survey on secure search over encrypted data on the cloud

Pham

Woodworth

Salehi

2019

Concurrency and Computation

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Cloud computing has become a potential resource for businesses and individuals to outsource their data to remote but highly accessible servers. However, the potential of cloud services has not been fully realized due to users concerns about data privacy and security. User-side encryption techniques can be employed to mitigate the security concerns, but once the data is encrypted, no processing (eg, searching) can be performed on the outsourced data. Searchable Encryption (SE) techniques have been widely studied to enable searching on the data while they are encrypted. These techniques enable various types of search on the encrypted data and offer different levels of security. While these techniques enable different search types and vary in details, they share similarities in their components and architectures. In this paper, we provide a comprehensive survey on different secure search techniques, a high-level architecture for these systems, and an analysis of their performance and security level. KEYWORDScloud security, encrypted search, search over encrypted data, survey INTRODUCTIONAs cloud computing becomes prevalent, more cloud-based solutions are being developed and widely used in different applications. Companies that have adopted cloud storage solutions are reported to gain a competitive edge against those that have not. 1Cloud computing is favored due to its many advantages, including convenience and accessibility, consistent back ups to reducing the burden of local storage, and saving capital expenditure on in-house hardware and software maintenance. 2 However, public cloud storage services may be utilized by multi-tenant customers who store large amounts of potentially sensitive data on the cloud. Using cloud storage implies losing full control over data and delegating it to the cloud administrators, exposing the data to potential external and internal attacks, 3,4 which can be devastating for organizations that rely on confidentiality of their data (eg, financial corporations).These problems have made businesses concerned about outsourcing their data to the cloud and utilizing its potential. 5,6 For instance, a medical center that owns patients' health records cannot outsource its data to a cloud that is vulnerable to attacks, due to legal regulations. 7 In another instance, a law enforcement agency that keeps sensitive criminal records will hesitate to use cloud storage because of similar concerns.this approach remains impractical. Therefore, searchable encryption systems (eg, see other works 12-15 ) have been introduced to cope with this problem. These systems ideally allow the encrypted data to be searched without revealing the data and search query. Hence, they relieve concerns about data confidentiality in the cloud. Efforts to create searchable encryption systems date back to 2000 with work by Song et al. 11 Since then, numerous research works have been undertaken to enable different types of searchable encryption. Although these systems differ in their search approaches, security level, and perf...

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Massive Data Analysis: Tasks, Tools, Applications, and Challenges

Cited by 14 publications

References 28 publications

Creativity Forward: A Framework That Integrates Data Analysis Techniques to Foster Creativity Within the Creative Process in User Experience Contexts

Creativity Forward: A Framework That Integrates Data Analysis Techniques to Foster Creativity Within the Creative Process in User Experience Contexts

A Simple Semantic-Based Data Storage Layout for Querying Point Clouds

Survey on secure search over encrypted data on the cloud

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