168 research outputs found

    Digital Image Access & Retrieval

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    The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

    Creating Network Attack Priority Lists by Analyzing Email Traffic Using Predefined Profiles

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    Networks can be vast and complicated entities consisting of both servers and workstations that contain information sought by attackers. Searching for specific data in a large network can be a time consuming process. Vast amounts of data either passes through or is stored by various servers on the network. However, intermediate work products are often kept solely on workstations. Potential high value targets can be passively identified by comparing user email traffic against predefined profiles. This method provides a potentially smaller footprint on target systems, less human interaction, and increased efficiency of attackers. Collecting user email traffic and comparing each word in an email to a predefined profile, or a list of key words of interest to the attacker, can provide a prioritized list of systems containing the most relevant information. This research uses two experiments. The functionality experiment uses randomly generated emails and profiles, demonstrating MAPS (Merritt\u27s Adaptive Profiling System)ability to accurately identify matches. The utility experiment uses an email corpus and meaningful profiles, further demonstrating MAPS ability to accurately identify matches with non-random input. A meaningful profile is a list of words bearing a semantic relationship to a topic of interest to the attacker. Results for the functionality experiment show MAPS can parse randomly generated emails and identify matches with an accuracy of 99 percent or above. The utility experiment using an email corpus with meaningful profiles, shows slightly lower accuracies of 95 percent or above. Based upon the match results, network attack priority lists are generated. A network attack priority list is an ordered list of systems, where the potentially highest value systems exhibit the greatest fit to the profile. An attacker then uses the list when searching for target information on the network to prioritize the systems most likely to contain useful data

    A Child-Driven Metadata Schema: A Holistic Analysis of Children\u27s Cognitive Processes During Book Selection

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    The purpose of this study was to construct a child-driven metadata schema by understanding children\u27s cognitive processes and behaviors during book selection. Existing knowledge organization systems including metadata schemas and previous literature in the metadata domain have shown that there is a no specialized metadata schema that describes children\u27s resources that also is developed by children. It is clear that children require a new or alternative child-driven metadata schema. Child-driven metadata elements reflected the children\u27s cognitive perceptions that could allow children to intuitively and easily find books in an online cataloging system. The literature of development of literacy skills claims that the positive experiences of selecting books empower children\u27s motivation for developing literacy skills. Therefore, creating a child-driven metadata schema not only contributes to the improvement of knowledge organization systems reflecting children\u27s information behavior and cognitive process, but also improves children\u27s literacy and reading skills. Broader research questions included what metadata elements do children like to use? What elements should a child-driven metadata schema include? In order to answer these research questions, a triangulated qualitative research design consisting of questionnaires, paired think-aloud, interview, and diaries were used with 22 child participants between the ages of 6 and 9. A holistic understanding of the children\u27s cognitive processes during book selection as a foundation of a child-driven metadata schema displays an early stage of an ontological contour for a children\u27s knowledge organization system. A child-driven metadata schema constructed in this study is apt to include different metadata elements from those metadata elements existing in current cataloging standards. A child-driven metadata schema includes five classes such as story/subject, character, illustration, physical characteristics, and understandability, and thirty three metadata elements such as character\u27s names and images, book cover\u27s color, shape, textured materials, engagement element, and tone. In addition, the analysis of the relationship between emergent emotional vocabularies and cognitive factors and facets illustrated the important role of emotion and attention in children\u27s information processing and seeking behaviors

    Development of linguistic linked open data resources for collaborative data-intensive research in the language sciences

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    Making diverse data in linguistics and the language sciences open, distributed, and accessible: perspectives from language/language acquistiion researchers and technical LOD (linked open data) researchers. This volume examines the challenges inherent in making diverse data in linguistics and the language sciences open, distributed, integrated, and accessible, thus fostering wide data sharing and collaboration. It is unique in integrating the perspectives of language researchers and technical LOD (linked open data) researchers. Reporting on both active research needs in the field of language acquisition and technical advances in the development of data interoperability, the book demonstrates the advantages of an international infrastructure for scholarship in the field of language sciences. With contributions by researchers who produce complex data content and scholars involved in both the technology and the conceptual foundations of LLOD (linguistics linked open data), the book focuses on the area of language acquisition because it involves complex and diverse data sets, cross-linguistic analyses, and urgent collaborative research. The contributors discuss a variety of research methods, resources, and infrastructures. Contributors Isabelle Barrière, Nan Bernstein Ratner, Steven Bird, Maria Blume, Ted Caldwell, Christian Chiarcos, Cristina Dye, Suzanne Flynn, Claire Foley, Nancy Ide, Carissa Kang, D. Terence Langendoen, Barbara Lust, Brian MacWhinney, Jonathan Masci, Steven Moran, Antonio Pareja-Lora, Jim Reidy, Oya Y. Rieger, Gary F. Simons, Thorsten Trippel, Kara Warburton, Sue Ellen Wright, Claus Zin

    Development of Linguistic Linked Open Data Resources for Collaborative Data-Intensive Research in the Language Sciences

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    This book is the product of an international workshop dedicated to addressing data accessibility in the linguistics field. It is therefore vital to the book’s mission that its content be open access. Linguistics as a field remains behind many others as far as data management and accessibility strategies. The problem is particularly acute in the subfield of language acquisition, where international linguistic sound files are needed for reference. Linguists' concerns are very much tied to amount of information accumulated by individual researchers over the years that remains fragmented and inaccessible to the larger community. These concerns are shared by other fields, but linguistics to date has seen few efforts at addressing them. This collection, undertaken by a range of leading experts in the field, represents a big step forward. Its international scope and interdisciplinary combination of scholars/librarians/data consultants will provide an important contribution to the field

    Linked Open Data - Creating Knowledge Out of Interlinked Data: Results of the LOD2 Project

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    Database Management; Artificial Intelligence (incl. Robotics); Information Systems and Communication Servic

    The Pilot Land Data System: Report of the Program Planning Workshops

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    An advisory report to be used by NASA in developing a program plan for a Pilot Land Data System (PLDS) was developed. The purpose of the PLDS is to improve the ability of NASA and NASA sponsored researchers to conduct land-related research. The goal of the planning workshops was to provide and coordinate planning and concept development between the land related science and computer science disciplines, to discuss the architecture of the PLDs, requirements for information science technology, and system evaluation. The findings and recommendations of the Working Group are presented. The pilot program establishes a limited scale distributed information system to explore scientific, technical, and management approaches to satisfying the needs of the land science community. The PLDS paves the way for a land data system to improve data access, processing, transfer, and analysis, which land sciences information synthesis occurs on a scale not previously permitted because of limits to data assembly and access
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