Conferences related to Keyword search

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2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)

ICSE is the premier forum for researchers to present and discuss the most recent innovations, trends, outcomes, experiences, and challenges in the field of software engineering. The scope is broad and includes all original and unpublished results of empirical, conceptual, experimental, and theoretical software engineering research.


2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2019 Winter Simulation Conference (WSC)

WSC is the premier international forum for disseminating recent advances in the field of system simulation. In addition to a technical program of unsurpassed scope and quality, WSC provides the central meeting for practitioners, researchers, and vendors.


ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

ICASSP is the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class presentations by internationally renowned speakers, cutting-edge session topics and provide a fantastic opportunity to network with like-minded professionals from around the world.


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Periodicals related to Keyword search

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Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...


Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


Computers, IEEE Transactions on

Design and analysis of algorithms, computer systems, and digital networks; methods for specifying, measuring, and modeling the performance of computers and computer systems; design of computer components, such as arithmetic units, data storage devices, and interface devices; design of reliable and testable digital devices and systems; computer networks and distributed computer systems; new computer organizations and architectures; applications of VLSI ...


Information Forensics and Security, IEEE Transactions on

Research on the fundamental contributions and the mathematics behind information forensics, information seurity, surveillance, and systems applications that incorporate these features.


Intelligent Systems, IEEE

IEEE Intelligent Systems, a bimonthly publication of the IEEE Computer Society, provides peer-reviewed, cutting-edge articles on the theory and applications of systems that perceive, reason, learn, and act intelligently. The editorial staff collaborates with authors to produce technically accurate, timely, useful, and readable articles as part of a consistent and consistently valuable editorial product. The magazine serves software engineers, systems ...


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Most published Xplore authors for Keyword search

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Xplore Articles related to Keyword search

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Santa Monica Becomes An Electronic City

Delicate Balance: Technics, Culture and Consequences, 1989

None


Efficient Keyword Search for SLCA in Parallel XML Databases

2011 Eighth Web Information Systems and Applications Conference, 2011

Keyword search is a wildly popular way for querying XML document. However, the increasing volume of XML data poses new challenges to keyword search processing. Parallel database is an efficient solution for this problem. In this paper, we study the problem of effective keyword search for SLCA (Smallest lower common ancestor) in parallel XML databases. We propose two efficient algorithm ...


Effective XML keyword query processing

2017 International conference of Electronics, Communication and Aerospace Technology (ICECA), 2017

Keyword search query processing is considered as the most promising way of information retrieval over XML data in present days as it relieves user from understanding complex schemas of XML document and writing difficult queries using XPath and XQuery. Till date various query processing techniques have been proposed to get meaningful results through keyword search using LCA (Lowest Common Ancestor) ...


Research on Ontology-Based Semantic Similarity Computation

2010 International Conference on Machine Vision and Human-machine Interface, 2010

This paper we present a method for computing similarity between different concepts. Ontology has the good hierarchical structure of concepts and the support of logical reasoning, and semantic information can be realized through the semantic relationship of concepts. Ontology technology can be well applied to information retrieval. Ontology-based information retrieval is different from the traditional keyword search. Semantic retrieval can ...


Privacy-Preserving Attribute-Based Keyword Search in Shared Multi-owner Setting

IEEE Transactions on Dependable and Secure Computing, None

Ciphertext-Policy Attribute-Based Keyword Search (CP-ABKS) facilitates search queries and supports fine-grained access control over encrypted data in the cloud. However, prior CP-ABKS schemes were designed to support unshared multi- owner setting, and cannot be directly applied in the shared multi-owner setting (where each record is accredited by a fixed number of data owners), without incurring high computational and storage costs. ...


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Educational Resources on Keyword search

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IEEE-USA E-Books

  • Santa Monica Becomes An Electronic City

    None

  • Efficient Keyword Search for SLCA in Parallel XML Databases

    Keyword search is a wildly popular way for querying XML document. However, the increasing volume of XML data poses new challenges to keyword search processing. Parallel database is an efficient solution for this problem. In this paper, we study the problem of effective keyword search for SLCA (Smallest lower common ancestor) in parallel XML databases. We propose two efficient algorithm SONB (Scan once with no buffer) and MSOP (Merge strategy based on ordered partition) to compute the SLCA efficiently in the parallel environment. We have performed an extensive experimental study and the results show that our proposed approach achieves high efficiency for the keyword search.

  • Effective XML keyword query processing

    Keyword search query processing is considered as the most promising way of information retrieval over XML data in present days as it relieves user from understanding complex schemas of XML document and writing difficult queries using XPath and XQuery. Till date various query processing techniques have been proposed to get meaningful results through keyword search using LCA (Lowest Common Ancestor) semantic under tree based approach. Amongst many such LCA based techniques which have been proposed to get more accurate and meaningful results SLCA (Smallest LCA) and ELCA (Exclusive LCA), have considered being the most popular ones. However due to AND-semantic constraints of LCA based techniques, SLCA or ELCA results into NULL for keyword queries involving missing elements and provides unintended results if the technique returns root element of the document. To address these issues, we propose an effective XML keyword query processing technique. In this paper we present the proposed technique based on ELCA query semantic which returns the meaningful results when ELCA based technique results into NULL or document root element thereby providing better information discovery over XML data. The proposed technique can also be applied to SLCA based techniques to get similar SLCA based meaningful results.

  • Research on Ontology-Based Semantic Similarity Computation

    This paper we present a method for computing similarity between different concepts. Ontology has the good hierarchical structure of concepts and the support of logical reasoning, and semantic information can be realized through the semantic relationship of concepts. Ontology technology can be well applied to information retrieval. Ontology-based information retrieval is different from the traditional keyword search. Semantic retrieval can be realized because Ontology knowledge base strengthens the intrinsic link of the concepts and the implied and unclear information can be deduced through logical reasoning. Our results show that the general framework is feasible and this method is applicable across different concepts.

  • Privacy-Preserving Attribute-Based Keyword Search in Shared Multi-owner Setting

    Ciphertext-Policy Attribute-Based Keyword Search (CP-ABKS) facilitates search queries and supports fine-grained access control over encrypted data in the cloud. However, prior CP-ABKS schemes were designed to support unshared multi- owner setting, and cannot be directly applied in the shared multi-owner setting (where each record is accredited by a fixed number of data owners), without incurring high computational and storage costs. In addition, due to privacy concerns on access policies, most existing schemes are vulnerable to off-line keyword-guessing attacks if the keyword space is of polynomial size. Furthermore, it is difficult to identify malicious users who leak the secret keys when more than one data user has the same subset of attributes. In this paper, we present a privacy-preserving CP-ABKS system with hidden access policy in Shared Multi-owner setting (basic ABKS-SM system), and demonstrate how it is improved to support malicious user tracing (modified ABKS-SM system). We then prove that the proposed ABKS-SM systems achieve selective security and resist off-line keyword-guessing attack in the generic bilinear group model. We also evaluate their performance using real-world datasets.

  • Inverted index and interval lists for keyword search

    Search operations have become quite indispensable in recent days and loads of research are being organized to store and process the indices required for search operations in a simple and effective manner. Whenever indices are stored, the space it occupies and the ease of access are to be taken care of. This paper briefly deals with the existing system - the inverted index, and discusses the limitations in using such a system. The paper then introduces a new and effective way to store and process indices, namely using interval lists which drastically reduces the storage space and improves the access time. The paper then introduces basic search algorithms that uses indices stored as interval lists. The paper also discusses the basic differences between the existing and proposed system and analyses the various scenarios where each system comes in handy.

  • An efficient semantic secure keyword based search scheme in cloud storage services

    Cloud data storage (Storage as a Service) is an important service of cloud computing it can also be referred as Infrastructure as a Service (IaaS). The data storage security problem is an important aspect of Quality of Service (QoS). In the existing cloud storage, the user stores his information in the encrypted format, preserving privacy. When a user wants to retrieve files through keyword search, the cloud storage server returns all matched data, which forces the user to decrypt all returned data. Decrypting all the returned data will result in depletion of CPU time and results in increased memory utilization. This paper proposes an efficient semantic secure keyword based search (ESSKS) scheme, which retrieves exact information needed by the user, ensuring that the same keyword does not always produce the same result, in user querying, reducing computational and communication overhead. This security mechanism also addresses the data integrity problem.

  • Hot-Chord: A Query Algorithm for Accelerating the Locating of Hot Resources

    Chord is a common circular P2P model with high routing efficiency and stable data inquiring. This paper proposes the Hot-Chord algorithm according to the fact that hot resources have occupied the majority of searching in the P2P system. Hot-Chord algorithm constructs an inner chord dynamically by using the nodes which hot resources is locating, to decrease the inquiring space; Nodes join or leave the inner chord adaptively according to the variation of resources searching rate. On the basis of theoretical analysis and experimental simulation, this paper certifies that the Hot-Chord algorithm has not only the better searching efficiency in hot resources inquiring but also the lower the average number of hops in finding resources than the original Chord and some improved algorithms.

  • Creating routing plan for keyword query

    Keyword search is an inherent example for searching linked data sources on the web. The proposed work tries to route keywords only to relevant sources. This would also reduce the high cost of processing keyword search queries over all sources. This proposed work also tries to compute top-k routing places based on their potentials to contain results for a given keyword query. The number of potential results may increase exponentially with the number of sources and links between them. Most of the results may be not necessary especially when they are not relevant to the user. The proposed work uses to solve the problem of keyword search over large number of linked and structured data source by using keyword expansion.

  • Evaluating the Reuse of Learning Content through a Segmentation Approach

    There is an increasingly number of worldwide available content on the Web, which could be reused to support learning processes. However, Web content is getting more and more structured as multimedia files and reusing it implies on using the whole file, which limits its applicability and the return on investment of its development. So, an interesting approach is the segmentation of content, structuring it on reusable segments. Furthermore, once created, these segments can be reused in an easy way in different educational contexts. This paper discusses the segmentation process and presents the results obtained from a case study conducted using a prototype to evaluate this approach.



Standards related to Keyword search

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