27,318 research outputs found
Managing Compressed Structured Text
[Definition]: Compressing structured text is the problem of creating a reduced-space representation from which the original
data can be re-created exactly. Compared to plain text compression, the goal is to take advantage of the structural
properties of the data. A more ambitious goal is that of being able of manipulating this text in compressed form,
without decompressing it. This entry focuses on compressing, navigating, and searching structured text, as those
are the areas where more advances have been made
Efficient data representation for XML in peer-based systems
Purpose - New directions in the provision of end-user computing experiences mean that the best way to share data between small mobile computing devices needs to be determined. Partitioning large structures so that they can be shared efficiently provides a basis for data-intensive applications on such platforms. The partitioned structure can be compressed using dictionary-based approaches and then directly queried without firstly decompressing the whole structure. Design/methodology/approach - The paper describes an architecture for partitioning XML into structural and dictionary elements and the subsequent manipulation of the dictionary elements to make the best use of available space. Findings - The results indicate that considerable savings are available by removing duplicate dictionaries. The paper also identifies the most effective strategy for defining dictionary scope. Research limitations/implications - This evaluation is based on a range of benchmark XML structures and the approach to minimising dictionary size shows benefit in the majority of these. Where structures are small and regular, the benefits of efficient dictionary representation are lost. The authors' future research now focuses on heuristics for further partitioning of structural elements. Practical implications - Mobile applications that need access to large data collections will benefit from the findings of this research. Traditional client/server architectures are not suited to dealing with high volume demands from a multitude of small mobile devices. Peer data sharing provides a more scalable solution and the experiments that the paper describes demonstrate the most effective way of sharing data in this context. Social implications - Many services are available via smartphone devices but users are wary of exploiting the full potential because of the need to conserve battery power. The approach mitigates this challenge and consequently expands the potential for users to benefit from mobile information systems. This will have impact in areas such as advertising, entertainment and education but will depend on the acceptability of file sharing being extended from the desktop to the mobile environment. Originality/value - The original work characterises the most effective way of sharing large data sets between small mobile devices. This will save battery power on devices such as smartphones, thus providing benefits to users of such devices
BlogForever: D3.1 Preservation Strategy Report
This report describes preservation planning approaches and strategies recommended by the BlogForever project as a core component of a weblog repository design. More specifically, we start by discussing why we would want to preserve weblogs in the first place and what it is exactly that we are trying to preserve. We further present a review of past and present work and highlight why current practices in web archiving do not address the needs of weblog preservation adequately. We make three distinctive contributions in this volume: a) we propose transferable practical workflows for applying a combination of established metadata and repository standards in developing a weblog repository, b) we provide an automated approach to identifying significant properties of weblog content that uses the notion of communities and how this affects previous strategies, c) we propose a sustainability plan that draws upon community knowledge through innovative repository design
XML Schema-based Minification for Communication of Security Information and Event Management (SIEM) Systems in Cloud Environments
XML-based communication governs most of today's systems communication, due to
its capability of representing complex structural and hierarchical data.
However, XML document structure is considered a huge and bulky data that can be
reduced to minimize bandwidth usage, transmission time, and maximize
performance. This contributes to a more efficient and utilized resource usage.
In cloud environments, this affects the amount of money the consumer pays.
Several techniques are used to achieve this goal. This paper discusses these
techniques and proposes a new XML Schema-based Minification technique. The
proposed technique works on XML Structure reduction using minification. The
proposed technique provides a separation between the meaningful names and the
underlying minified names, which enhances software/code readability. This
technique is applied to Intrusion Detection Message Exchange Format (IDMEF)
messages, as part of Security Information and Event Management (SIEM) system
communication hosted on Microsoft Azure Cloud. Test results show message size
reduction ranging from 8.15% to 50.34% in the raw message, without using
time-consuming compression techniques. Adding GZip compression to the proposed
technique produces 66.1% shorter message size compared to original XML
messages.Comment: XML, JSON, Minification, XML Schema, Cloud, Log, Communication,
Compression, XMill, GZip, Code Generation, Code Readability, 9 pages, 12
figures, 5 tables, Journal Articl
The SP theory of intelligence: benefits and applications
This article describes existing and expected benefits of the "SP theory of
intelligence", and some potential applications. The theory aims to simplify and
integrate ideas across artificial intelligence, mainstream computing, and human
perception and cognition, with information compression as a unifying theme. It
combines conceptual simplicity with descriptive and explanatory power across
several areas of computing and cognition. In the "SP machine" -- an expression
of the SP theory which is currently realized in the form of a computer model --
there is potential for an overall simplification of computing systems,
including software. The SP theory promises deeper insights and better solutions
in several areas of application including, most notably, unsupervised learning,
natural language processing, autonomous robots, computer vision, intelligent
databases, software engineering, information compression, medical diagnosis and
big data. There is also potential in areas such as the semantic web,
bioinformatics, structuring of documents, the detection of computer viruses,
data fusion, new kinds of computer, and the development of scientific theories.
The theory promises seamless integration of structures and functions within and
between different areas of application. The potential value, worldwide, of
these benefits and applications is at least $190 billion each year. Further
development would be facilitated by the creation of a high-parallel,
open-source version of the SP machine, available to researchers everywhere.Comment: arXiv admin note: substantial text overlap with arXiv:1212.022
On inverted index compression for search engine efficiency
Efficient access to the inverted index data structure is a key aspect for a search engine to achieve fast response times to usersâ queries . While the performance of an information retrieval (IR) system can be enhanced through the compression of its posting lists, there is little recent work in the literature that thoroughly compares and analyses the performance of modern integer compression schemes across different types of posting information (document ids, frequencies, positions). In this paper, we experiment with different modern integer compression algorithms, integrating these into a modern IR system. Through comprehensive experiments conducted on two large, widely used document corpora and large query sets, our results show the benefit of compression for different types of posting information to the space- and time-efficiency of the search engine. Overall, we find that the simple Frame of Reference compression scheme results in the best query response times for all types of posting information. Moreover, we observe that the frequency and position posting information in Web corpora that have large volumes of anchor text are more challenging to compress, yet compression is beneficial in reducing average query response times
Challenging Ubiquitous Inverted Files
Stand-alone ranking systems based on highly optimized inverted file structures are generally considered âtheâ solution for building search engines. Observing various developments in software and hardware, we argue however that IR research faces a complex engineering problem in the quest for more flexible yet efficient retrieval systems. We propose to base the development of retrieval systems on âthe database approachâ: mapping high-level declarative specifications of the retrieval process into efficient query plans. We present the Mirror DBMS as a prototype implementation of a retrieval system based on this approach
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