@article {254,
	title = {Augmenting digital libraries with web-based visualizations},
	journal = {Journal of Digital Information Management},
	volume = {8},
	year = {2010},
	note = {Cited By (since 1996):1Export Date: 10 July 2014},
	month = {2010},
	pages = {377 - 386},
	abstract = {Digital libraries in their current form are bounded by their ineffcient webpage-based user interface paradigm, and even the most knowledgeable researchers can get lost in the large amount of published material available. A paper and its immediate references are displayed on a single webpage. Unfortunately, it is not readily apparent where the paper belongs in the greater context of a research field. Our goal was to develop, test, and iteratively improve the effectiveness of a web-based application, PaperCube, designed to augment and enhance a researcher{\textquoteright}s interaction with digital libraries through the use of interactive visualizations of bibliographic meta data. The visualizations set out to show different levels of detail and aspects of a paper{\textquoteright}s citation network. A primary concern was to ensure that while switching visualizations, the viewed paper or author remained focused at all times. PaperCube was validated through a user study that showed that it helped users who are trying to explore a field of research. In particular, PaperCube was shown to reduce the "cognitive load" put on a researcher and aid the "discoverability" of new research material.},
	keywords = {Digital libraries, Graphical user interfaces, Navigation, PaperCube, Web-based visualization},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-79960682007\&partnerID=40\&md5=746cf2e1545b3dd8f0d1697f5673e6e8},
	author = {Bergstr{\"o}m, P. and Atkinson, D.C.}
}
@article {231,
	title = {Rule based autonomous citation mining with tierl},
	journal = {Journal of Digital Information Management},
	volume = {8},
	year = {2010},
	note = {Cited By (since 1996):9Export Date: 10 July 2014},
	month = {2010},
	pages = {196 - 204},
	abstract = {Citations management is an important task in managing digital libraries. Citations provide valuable information e.g., used in evaluating an author{\textquoteright}s influences or scholarly quality (the impact factor of research journals). But although a reliable and effective autonomous citation management is essential, manual citation management can be extremely costly. Automatic citation mining on the other hand is a non-trivial task mainly due to non-conforming citation styles, spelling errors and the difficulty of reliably extracting text from PDF documents. In this paper we propose a novel rule-based autonomous citation mining technique, to address this important task. We define a set of common heuristics that together allow to improve the state of the art in automatic citation mining. Moreover, by first disambiguating citations based on venues, our technique significantly enhances the correct discovery of citations. Our experiments show that the proposed approach is indeed able to overcome limitations of current leading citation indexes such as ISI Web of Knowledge, Citeseer and Google Scholar.},
	keywords = {Citation index, Citation mining, Digital libraries, Information extraction},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-79951786283\&partnerID=40\&md5=4fbea6129a6c4c727c3c0618ccbe6087},
	author = {Afzal, M.T. and Maurer, H. and Balke, W.-T. and Kulathuramaiyer, N.}
}
@article {191,
	title = {Where do the authors come from?},
	journal = {Journal of Digital Information Management},
	volume = {7},
	year = {2009},
	note = {Export Date: 10 July 2014},
	month = {2009},
	pages = {211 - 218},
	abstract = {Permanent growth of scientific publications makes bibliographic databases and digital libraries widespread. At the same time they are an object of research in their own right. In this paper we address the question of "where do the authors come from?" via language identification of the author names. This is a two-steps process which involves primary classification based on the statistical models of languages, and classification refinement achieved with the analysis of the co-author network built from the bibliographic records. A system for automatic language identification presented here handles 14 different languages and requires no dictionary of names for traing. The statistical models are built from the general purpose corpora for all Western European, Chinese, Japanese and Turkish languages. The system is fine tuned to achieve precision and recall above 90\% for many languages, and provides better performance than some other systems aiming at the language identification of personal names. Tests on the DBLP data set have shown that the extension of the language model with the co-author network helps to improve classification results, especially in cases of closely related languages and mixed names. They have also demonstrated the usability of the system in applications such as data cleaning and trends detection.},
	keywords = {Co-author network, DBLP database, Digital libraries, Language classification, Scientific publications},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-77953242477\&partnerID=40\&md5=d76b422a52e3bdf48f54dbd4ba5cd9c1},
	author = {Biryukov, M.}
}
@article {155,
	title = {Accessing heritage documents according to space criteria within digital libraries},
	journal = {Journal of Digital Information Management},
	volume = {6},
	year = {2008},
	note = {Export Date: 10 July 2014},
	month = {2008},
	pages = {102 - 117},
	abstract = {Local cultural heritage document collections are characterized by contents strongly attached to a territory and its associated land history. Our contribution aims at enhancing such a content retrieval process efficiently each time a query includes geographic criteria. We propose a unified model for a formal representation of geographic information. This geographic model allows space features to be described independently of their representation mode (text, graphics) in the documents. We have developed a prototype implementing geographic Information Extraction (IE) and geographic Information Retrieval (IR) processes. We process geographic IE with semantic techniques combined to classic IE approaches. Then, we implement geographic IR with intersections researching algorithms: these algorithms search for all geocoded entities in the documents collections indexes which intersect any entity in the user{\textquoteright}s query. This paper focuses on IR and Visualization proposals relying on the geospatial characteristics of cultural heritage corpora.},
	keywords = {Cultural heritage, Digital libraries, Geographic information retrieval and visualization, Geographic model, Non-structured documents},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-56849092298\&partnerID=40\&md5=199c3f9b17bf1a325e0c3fcc90160b17},
	author = {Marquesuza{\`a}, C. and Etcheverry, P. and Sallaberry, C. and Baziz, M.}
}
@article {153,
	title = {Classification of digital libraries - An e-business model-based approach},
	journal = {Journal of Digital Information Management},
	volume = {6},
	year = {2008},
	note = {Cited By (since 1996):1Export Date: 10 July 2014},
	month = {2008},
	pages = {71 - 80},
	abstract = {The impact of digital libraries on information processes steadily increases. Today, users may choose from a rapidly increasing number of digital libraries with various characteristics. Business models for digital libraries evolve from mere content providers to sophisticated service suppliers They offer a rich variety of information services combined with collaboration, e-learning and portal features. Traditional classification schemes for digital libraries do not sufficiently take this development into account or fail to meet it at all. In this paper we present a novel approach to the classification of digital libraries. It is based on business model characteristics with special emphasis on the evolution of digital libraries from content to information service providers. Our classification approach helps suppliers to communicate benefits and features of their libraries more effectively. It also supports customers when selecting an appropriate digital library.},
	keywords = {Digital libraries, Digital libraries evaluation, Information processing},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-56849121020\&partnerID=40\&md5=5183b0da70e4e961e3e8e1e49f3af703},
	author = {Markscheffel, B. and Fischer, D. and Stelzer, D.}
}
@article {64,
	title = {Semantic, constraint \& preference based multimedia presentation authoring},
	journal = {Journal of Digital Information Management},
	volume = {4},
	year = {2006},
	note = {Cited By (since 1996):3Export Date: 10 July 2014},
	month = {2006},
	pages = {207 - 213},
	abstract = {We present in this paper an integrated system that allows the management and annotation of multimedia objects stored in MPEG-7/21 repositories, and the specification and semi-automatic generation of multimedia presentations based on the content relationships that exist between the multimedia objects. This system is the outcome of the collaboration between the Technical University of Crete (TUC-MUSIC) and the University of Milan (UNIMI) in the CoCoMA (Content and Context Aware Multimedia Content Retrieval, Delivery and Presentation) project of the DELOS II European Network of Excellence on Digital Libraries. The resulting system is one of the main components of the CoCoMA infrastructure that aims to provide content- and context-aware rich interactive multimedia presentations by controlling data fusion and metadata reuse. The integrated system utilizes the SyMPA management and presentation authoring system developed by UNIMI and the DS-MIRF framework developed by TUC-MUSIC.},
	keywords = {Authoring tools, Digital libraries, Multimedia presentations, Multimedia standards},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-33845937945\&partnerID=40\&md5=762148820f31cebc540800656d2bbd38},
	author = {Tsinaraki, C. and Perego, A. and Polydoros, P. and Syntzanaki, A. and Martin, A. and Christodoulakis, S.}
}
