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2016 IEEE Tenth International Conference on Semantic Computing (ICSC)

4-6 Feb. 2016

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Displaying Results 1 - 25 of 112
  • [Front cover]

    Publication Year: 2016, Page(s): C4
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  • [Title page i]

    Publication Year: 2016, Page(s): i
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  • [Title page iii]

    Publication Year: 2016, Page(s): iii
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  • [Copyright notice]

    Publication Year: 2016, Page(s): iv
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  • Table of contents

    Publication Year: 2016, Page(s):v - xiii
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  • Message from the Program Chairs

    Publication Year: 2016, Page(s): xiv
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  • Organizing Committee

    Publication Year: 2016, Page(s):xv - xvi
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  • Program Committee

    Publication Year: 2016, Page(s):xvii - xix
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  • Message from the ICSC-SCKNE'16  Program Chairs

    Publication Year: 2016, Page(s): xx
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  • ICSC-SCKNE'16  Program Committee

    Publication Year: 2016, Page(s): xxi
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  • Message from the ICSC-SMM'16 Program Chairs

    Publication Year: 2016, Page(s): xxii
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  • ICSC-SMM'16 Program Committee

    Publication Year: 2016, Page(s): xxiii
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  • Message from the IEEE-SCSN 2016 Program Chairs

    Publication Year: 2016, Page(s): xxiv
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  • IEEE-SCSN 2016 Program Committee

    Publication Year: 2016, Page(s): xxv
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  • Message from the ICSC- BBD'16 Program Chairs

    Publication Year: 2016, Page(s): xxvi
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  • ICSC- BBD'16 Program Committee

    Publication Year: 2016, Page(s): xxvii
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  • Keynotes

    Publication Year: 2016, Page(s):xxviii - xxxiii
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (202 KB)

    Provides an abstract for each of the keynote presentations and may include a brief professional biography of each View full abstract»

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  • Semantic Document Clustering Using a Similarity Graph

    Publication Year: 2016, Page(s):1 - 8
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (201 KB) | HTML iconHTML

    Document clustering addresses the problem of identifying groups of similar documents without human supervision. Unlike most existing solutions that perform document clustering based on keywords matching, we propose an algorithm that considers the meaning of the terms in the documents. For example, a document that contains the words "dog" and "cat" multiple times may be placed in the same category ... View full abstract»

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  • Extracting Semantics from Legacy Scientific Workflows

    Publication Year: 2016, Page(s):9 - 16
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (213 KB) | HTML iconHTML

    In this paper we present a method that uses the Workflow Instrumentation for structure Extraction (WISE) combined with the SemanticMap methods to process ad-hoc legacy workflows written in Python and produce a mapping of the workflow structural skeleton to a domain ontology. The method provides the foundation for searching through scientific workflows with conceptual queries. View full abstract»

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  • Object Recognition by Distortion-Free Graph Embedding and Random Forest

    Publication Year: 2016, Page(s):17 - 23
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (725 KB) | HTML iconHTML

    Error tolerant graph matching is required not only in many realistic object recognition scenarios, but also in different domains such as document analysis and mechanical drawings. This paper presents such a technique using a distortion-free graph embedding, reformulating the problem as that of finding error-tolerant point matching in the geometric space. The embedding works by finding the distance... View full abstract»

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  • Effective Tooling for Linked Data Publishing in Scientific Research

    Publication Year: 2016, Page(s):24 - 31
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (571 KB) | HTML iconHTML

    Challenges that make it difficult to find, share, and combine published data, such as data heterogeneity and resource discovery, have led to increased adoption of semantic data standards and data publishing technologies. To make data more accessible, interconnected and discoverable, some domains are being encouraged to publish their data as Linked Data. Consequently, this trend greatly increases t... View full abstract»

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  • Improved Spatial Pyramid Matching for Sports Image Classification

    Publication Year: 2016, Page(s):32 - 38
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (682 KB) | HTML iconHTML

    In the study on sports image classification, the characteristics of human pose increasingly raise concerns of researchers. However, the same posture for human may be resulted from different scenes and scene objects that express diverse action states and meanings. Thus, combination of human pose and event scenes shall be considered so as to improve performance of sports image classification. In rec... View full abstract»

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  • High-Level Surveillance Event Detection Using an Interval-Based Query Language

    Publication Year: 2016, Page(s):39 - 46
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (316 KB) | HTML iconHTML

    We propose a language based on relational algebra extended by intervals for detecting high-level surveillance events from a video stream. The operators we introduce for describing temporal constraints are based on the well-known Allen's interval relationships. The semantics of our language are clearly defined and we illustrate its usefulness by expressing typical events in it and showing the promi... View full abstract»

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  • The Mobile Audio Ontology: Experiencing Dynamic Music Objects on Mobile Devices

    Publication Year: 2016, Page(s):47 - 54
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1015 KB) | HTML iconHTML

    This paper is about the Mobile Audio Ontology, a semantic audio framework for the design of novel music consumption experiences on mobile devices. The framework is based on the concept of the Dynamic Music Object which is an amalgamation of audio files, structural and analytical information extracted from the audio, and information about how it should be rendered in realtime. The Mobile Audio Onto... View full abstract»

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  • Negative Correlation Discovery for Big Multimedia Data Semantic Concept Mining and Retrieval

    Publication Year: 2016, Page(s):55 - 62
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (234 KB) | HTML iconHTML

    With massive amounts of data producing each day in almost every field, traditional data processing techniques have become more and more inadequate. However, the research of effectively managing and retrieving these big data is still under development. Multimedia high-level semantic concept mining and retrieval in big data is one of the most challenging research topics, which requires joint efforts... View full abstract»

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