@techreport{2738,
  author       = {{Dimant, Eugen and Krieger, Tim and Redlin, Margarete}},
  publisher    = {{Center for Economic Studies and Ifo Institute (CESifo), Munich}},
  title        = {{{A Crook is a Crook ... But is He Still a Crook Abroad? On the Effect of Immigration on Destination-Country Corruption}}},
  volume       = {{5032}},
  year         = {{2014}},
}

@inproceedings{1134,
  abstract     = {{This paper focuses on the first step in combining prescriptive analytics with scenario techniques in order to provide strategicdevelopment after the useof InSciTe, a data prescriptive analytics application. InSciTe supports the improvement of researchers‘ individual performance by recommending new research directions. Standardized influential factors are presented as a foundation for automated scenario modelling such as the prototypical report generation function of InSciTe. Additionally, a use-case is shown which validatesthe potential of the standardized influential factors for raw scenario development.}},
  author       = {{Weber, Jens and Minhee, Cho and Lee, Mikyoung and Song, Sa-kwang and Geierhos, Michaela and Jung, Hanmin}},
  booktitle    = {{Proceedings of the First International Workshop on Patent Mining and Its Applications (IPaMin 2014) co-located with Konvens 2014}},
  editor       = {{Jung, Hanmin and Mandl, Thomas and Womsen-Hacker, Christa and Xu, Shuo}},
  issn         = {{16130073}},
  keywords     = {{Standardized Influential Factors, Prescriptive Analytics, Role Model Group, Scenario Technique}},
  location     = {{Hildesheim, Germany}},
  publisher    = {{CEUR-WS.org}},
  title        = {{{System Thinking: Crafting Scenarios for Prescriptive Analytics}}},
  volume       = {{1292}},
  year         = {{2014}},
}

@inproceedings{1135,
  abstract     = {{In this paper, we describe our system developed for the GErman SenTiment AnaLysis shared Task (GESTALT) for participation in the Maintask 2: Subjective Phrase and Aspect Extraction from Product Reviews. We present a tool, which identifies subjective and aspect phrases in German product reviews. For the recognition of subjective phrases, we pursue a lexicon-based approach. For the extraction of aspect phrases from the reviews, we consider two possible ways: Besides the subjectivity and aspect look-up, we also implemented a method to establish which subjective phrase belongs to which aspect. The system achieves better results for the recognition of aspect phrases than for the subjective identification.}},
  author       = {{Dollmann, Markus and Geierhos, Michaela}},
  booktitle    = {{Workshop Proceedings of the 12th Edition of the KONVENS Conference}},
  editor       = {{Faaß, Gertrud and Ruppenhofer, Josef}},
  isbn         = {{978-3-934105-47-8}},
  keywords     = {{corpus linguistics, sentiment analysis}},
  location     = {{Hildesheim, Germany}},
  pages        = {{185--191}},
  publisher    = {{Universitätsverlag Hildesheim}},
  title        = {{{SentiBA: Lexicon-based Sentiment Analysis on German Product Reviews}}},
  year         = {{2014}},
}

@inproceedings{1137,
  abstract     = {{In this paper, we present a system which makes scientific data available following the linked open data principle using standards like RDF and URI as well as the popular D2R server (D2R) and the customizable D2RQ mapping language. Our scientific data sets include acronym data and expansions, as well as researcher data such as author name, affiliation, coauthors, and abstracts. The system can easily be extended to other records. Regarding this, a domain adaptation to patent mining seems possible. For this reason, obvious similarities and differences are presented here. The data set is collected from several different providers like publishing houses and digital libraries, which follow different standards in data format and structure. Most of them are not supporting semantic web technologies, but the legacy HTML standard. The integration of these large amounts of scientific data into the Semantic Web is challenging and it needs flexible data structures to access this information and interlink them. Based on these data sets, we will be able to derive a general technology trend as well as the individual research domain for each researcher. The goal of our Linked Open Data System for scientific data is to provide access to this data set for other researchers using the Web of Linked Data. Furthermore we implemented an application for visualization, which allows usto explorethe relations between single data sets.}},
  author       = {{Bäumer, Frederik Simon and Gim, Jangwon and Jeong, Do-Heon and Geierhos, Michaela and Jung, Hanmin}},
  booktitle    = {{Proceedings of the First International Workshop on Patent Mining and Its Applications (IPaMin 2014) co-located with Konvens 2014}},
  editor       = {{Jung, Hanmin and Mandl, Thomas and Womsen-Hacker, Christa and Xu, Shuo}},
  issn         = {{16130073}},
  keywords     = {{Linked Open Data, Researcher Data, Acronym Data, D2R}},
  location     = {{Hildesheim, Germany}},
  publisher    = {{CEUR-WS.org}},
  title        = {{{Linked Open Data System for Scientific Data Sets}}},
  volume       = {{1292}},
  year         = {{2014}},
}

@article{17962,
  author       = {{Albers, Sönke and Sureth-Sloane, Caren}},
  journal      = {{Business Research}},
  number       = {{2}},
  title        = {{{Editorial: What Is and What Is Not a Substantial Contribution?}}},
  volume       = {{5}},
  year         = {{2014}},
}

@inproceedings{5672,
  author       = {{Rauchecker, Gerhard and Yasasin, Emrah and Schryen, Guido}},
  booktitle    = {{11th International Conference on Trust, Privacy, and Security in Digital Business (TRUSTBUS)}},
  title        = {{{A Decision Support System for IT Security Incident Management}}},
  year         = {{2014}},
}

@article{5686,
  author       = {{Fink, Andreas and Kliewer, Natalia and Mattfeld, Dirk and Mönch, Lars and Rothlauf, Franz and Schryen, Guido and Suhl, Leena and Voß, Stefan}},
  journal      = {{Business & Information Systems Engineering (BISE)}},
  number       = {{1}},
  pages        = {{17--24}},
  publisher    = {{Gabler}},
  title        = {{{Model-based Decision Support in Manufacturing and Service Networks}}},
  volume       = {{6}},
  year         = {{2014}},
}

@article{5687,
  author       = {{Fink, Andreas and Kliewer, Natalia and Mattfeld, Dirk and Mönch, Lars and Rothlauf, Franz and Schryen, Guido and Suhl, Lena and Voß, Stefan}},
  journal      = {{Wirtschaftsinformatik}},
  number       = {{1}},
  pages        = {{21--29}},
  publisher    = {{Gabler}},
  title        = {{{Modellbasierte Entscheidungsunterstützung in Produktions- und Service-Netzwerken}}},
  volume       = {{56}},
  year         = {{2014}},
}

@techreport{6197,
  author       = {{Schryen, Guido}},
  title        = {{{The Epistemological Impact of Literature Reviews in Information Systems Research}}},
  year         = {{2014}},
}

@unpublished{442,
  abstract     = {{We present a new transformation of chosen-plaintext secure predicate encryption schemes with public index into chosen-ciphertext secure schemes. Our construction requires only a universal one-way hash function and is selectively secure in the standard model. The transformation is not generic but can be applied to various existing schemes constructed from bilinear groups. Using common structural properties of these schemes we provide an efficient and simple transformation without overhead in form of one-time signatures or message authentication codes as required in the known generic transformations.}},
  author       = {{Blömer, Johannes and Liske, Gennadij}},
  publisher    = {{Universität Paderborn}},
  title        = {{{Constructing CCA-secure predicate encapsulation schemes from CPA-secure schemes and universal one-way hash functions}}},
  year         = {{2014}},
}

@misc{418,
  author       = {{Pauck, Felix}},
  publisher    = {{Universität Paderborn}},
  title        = {{{Generierung von Eigenschaftsprüfern in einem Hardware/Software-Co-Verifikationsverfahren}}},
  year         = {{2014}},
}

@inproceedings{5573,
  author       = {{Yasasin, Emrah and Rauchecker, Gerhard and Prester, Julian and Schryen, Guido}},
  booktitle    = {{1st Workshop on Security in highly connected IT systems (SHCIS 14)}},
  title        = {{{A Fuzzy Security Investment Decision Support Model for Highly Distributed Systems}}},
  year         = {{2014}},
}

@article{5585,
  author       = {{Wex, Felix and Schryen, Guido and Feuerriegel, Stefan and Neumann, Dirk}},
  journal      = {{European Journal of Operational Research}},
  publisher    = {{Elsevier}},
  title        = {{{Emergency Response in Natural Disaster Management: Allocation and Scheduling of Rescue Units}}},
  year         = {{2014}},
}

@article{5614,
  abstract     = {{Natural disasters, including earthquakes, Tsunamis, floods, hurricanes, and volcanic eruptions, have caused tremendous harm and continue to threaten millions of humans and various infrastructure capabilities each year. In their efforts to take countermeasures against the threats posed by future natural disasters, the United Nations formulated the ?Hyogo Framework for Action?, which aims at assessing and reducing risk. This framework and a global review of disaster reduction initiatives of the United Nations acknowledge the need for information systems research contributions in addressing major challenges of natural disaster management. In this paper, we provide a review of the literature with regard to how information systems research has addressed risk assessment and reduction in natural disaster management. Based on the review we identify research gaps that are centered around the need for acquiring general knowledge on how to design IS artifacts for risk assessment and reduction. In order to close these gaps in further research, we develop a research agenda that follows the IS design science paradigm.}},
  author       = {{Schryen, Guido and Wex, Felix}},
  journal      = {{International Journal of Information Systems for Crisis Response and Management (IJISCRAM)}},
  keywords     = {{Natural Disaster Management, Risk Reduction, Hyogo Framework, IS Design Science, Literature review}},
  number       = {{1}},
  title        = {{{Risk Reduction in Natural Disaster Management Through Information Systems: A Literature review and an IS design science research agenda}}},
  volume       = {{6}},
  year         = {{2014}},
}

@article{5627,
  author       = {{Schryen, Guido and Hristova, Diana}},
  journal      = {{OR -Spectrum}},
  number       = {{1}},
  pages        = {{1--48}},
  publisher    = {{Springer}},
  title        = {{{Duality in fuzzy linear programming: A survey}}},
  volume       = {{37}},
  year         = {{2014}},
}

@article{5636,
  author       = {{Schryen, Guido}},
  journal      = {{Communications of the AIS}},
  title        = {{{Writing qualitative IS literature reviews ? Guidelines for synthesis, interpretation and guidance of research}}},
  year         = {{2014}},
}

@inproceedings{11746,
  abstract     = {{ "A method for nonstationary noise robust automatic speech recognition (ASR) is to first estimate the changing noise statistics and second clean up the features prior to recognition accordingly. Here, the first is accomplished by noise tracking in the spectral domain, while the second relies on Bayesian enhancement in the feature domain. In this way we take advantage of our recently proposed maximum a-posteriori based (MAP-B) noise power spectral density estimation algorithm, which is able to estimate the noise statistics even in time-frequency bins dominated by speech. We show that MAP-B noise tracking leads to an improved noise model estimate in the feature domain compared to estimating noise in speech absence periods only, if the bias resulting from the nonlinear transformation from the spectral to the feature domain is accounted for. Consequently, ASR results are improved, as is shown by experiments conducted on the Aurora IV database." }},
  author       = {{Chinaev, Aleksej and Puels, Marc and Haeb-Umbach, Reinhold}},
  booktitle    = {{11. ITG Fachtagung Sprachkommunikation (ITG 2014)}},
  title        = {{{Spectral Noise Tracking for Improved Nonstationary Noise Robust ASR}}},
  year         = {{2014}},
}

@inproceedings{11752,
  abstract     = {{ "In this contribution we derive a variational EM (VEM) algorithm for model selection in complex Watson mixture models, which have been recently proposed as a model of the distribution of normalized microphone array signals in the short-time Fourier transform domain. The VEM algorithm is applied to count the number of active sources in a speech mixture by iteratively estimating the mode vectors of the Watson distributions and suppressing the signals from the corresponding directions. A key theoretical contribution is the derivation of the MMSE estimate of a quadratic form involving the mode vector of the Watson distribution. The experimental results demonstrate the effectiveness of the source counting approach at moderately low SNR. It is further shown that the VEM algorithm is more robust w.r.t. used threshold values." }},
  author       = {{Drude, Lukas and Chinaev, Aleksej and Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}},
  booktitle    = {{39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)}},
  title        = {{{Source Counting in Speech Mixtures Using a Variational EM Approach for Complexwatson Mixture Models}}},
  year         = {{2014}},
}

@inproceedings{11753,
  abstract     = {{This contribution describes a step-wise source counting algorithm to determine the number of speakers in an offline scenario. Each speaker is identified by a variational expectation maximization (VEM) algorithm for complex Watson mixture models and therefore directly yields beamforming vectors for a subsequent speech separation process. An observation selection criterion is proposed which improves the robustness of the source counting in noise. The algorithm is compared to an alternative VEM approach with Gaussian mixture models based on directions of arrival and shown to deliver improved source counting accuracy. The article concludes by extending the offline algorithm towards a low-latency online estimation of the number of active sources from the streaming input data.}},
  author       = {{Drude, Lukas and Chinaev, Aleksej and Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}},
  booktitle    = {{14th International Workshop on Acoustic Signal Enhancement (IWAENC 2014)}},
  keywords     = {{Accuracy, Acoustics, Estimation, Mathematical model, Soruce separation, Speech, Vectors, Bayes methods, Blind source separation, Directional statistics, Number of speakers, Speaker diarization}},
  pages        = {{213--217}},
  title        = {{{Towards Online Source Counting in Speech Mixtures Applying a Variational EM for Complex Watson Mixture Models}}},
  year         = {{2014}},
}

@inproceedings{11814,
  abstract     = {{ "In this paper we present an algorithm for the unsupervised segmentation of a lattice produced by a phoneme recognizer into words. Using a lattice rather than a single phoneme string accounts for the uncertainty of the recognizer about the true label sequence. An example application is the discovery of lexical units from the output of an error-prone phoneme recognizer in a zero-resource setting, where neither the lexicon nor the language model (LM) is known. We propose a computationally efficient iterative approach, which alternates between the following two steps: First, the most probable string is extracted from the lattice using a phoneme LM learned on the segmentation result of the previous iteration. Second, word segmentation is performed on the extracted string using a word and phoneme LM which is learned alongside the new segmentation. We present results on lattices produced by a phoneme recognizer on the WSJCAM0 dataset. We show that our approach delivers superior segmentation performance than an earlier approach found in the literature, in particular for higher-order language models. " }},
  author       = {{Heymann, Jahn and Walter, Oliver and Haeb-Umbach, Reinhold and Raj, Bhiksha}},
  booktitle    = {{39th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014)}},
  title        = {{{Iterative Bayesian Word Segmentation for Unspuervised Vocabulary Discovery from Phoneme Lattices}}},
  year         = {{2014}},
}