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Concreteness of words has been studied extensively in psycholinguistic literature. A number of datasets have been created with average values for perceived concreteness of words. We show that we can train a regression model on these data, using word embeddings and morphological features, that can predict these concreteness values with high accuracy. We evaluate the model on 7 publicly available datasets. Only for a few small subsets of these datasets prediction of concreteness values are found in the literature. Our results clearly outperform the reported results for these datasets.
For the analysis of contract texts, validated model texts, such as model clauses, can be used to identify used contract clauses. This paper investigates how the similarity between titles of model clauses and headings extracted from contracts can be computed, and which similarity measure is most suitable for this. For the calculation of the similarities between title pairs we tested various variants of string similarity and token based similarity. We also compare two additional semantic similarity measures based on word embeddings using pre-trained embeddings and word embeddings trained on contract texts. The identification of the model clause title can be used as a starting point for the mapping of clauses found in contracts to verified clauses.
This paper deals with new job profiles in libraries, mainly systems librarians (German: Systembibliothekare), IT librarians (German: IT-Bibliothekare) and data librarians (German: Datenbibliothekare). It investigates the vacancies and requirements of these positions in the German-speaking countries by analyzing one hundred and fifty published job advertisements of OpenBiblioJobs between 2012-2016. In addition, the distribution of positions, institutional bearers, different job titles as well as time limits, scope of work and remuneration of the positions are evaluated. The analysis of the remuneration in the public sector in Germany also provides information on demands for a bachelor's or master's degree.
The average annual increase in job vacancies between 2012 and 2016 is 14.19%, confirming the need and necessity of these professional library profiles.
The higher remuneration of the positions in data management, in comparison to the systems librarian, proves the prerequisite of the master's degree and thus indicates a desideratum due to missing or few master's degree courses. Accordingly, the range of bachelor's degree courses (or IT-oriented major areas of study with optional compulsory modules in existing bachelor's degree courses) for systems and IT librarians must be further expanded. An alternative could also be modular education programs for librarians and information scientists with professional experience, as it is already the case for music librarians.
Das ProFormA-Aufgabenformat wurde eingeführt, um den Austausch von Programmieraufgaben zwischen beliebigen Autobewertern (Grader) zu ermöglichen. Ein Autobewerter führt im ProFormA-Aufgabenformat spezifizierte „Tests“ sequentiell aus, um ein vom Studierenden eingereichtes Programm zu prüfen. Für die Strukturierung und Darstellung der Testergebnisse existiert derzeit kein graderübergreifender Standard. Wir schlagen eine Erweiterung des ProFormA-Aufgabenformats um eine Hierarchie von Bewertungsaspekten vor, die nach didaktischen Aspekten gruppiert ist und entsprechende Testausführungen referenziert. Die Erweiterung wurde in Graja umgesetzt, einem Autobewerter für Java-Programme. Je nach gewünschter Detaillierung der Bewertungsaspekte sind Testausführungen in Teilausführungen aufzubrechen. Wir illustrieren unseren Vorschlag mit den Testwerkzeugen Compiler, dynamischer Softwaretest, statische Analyse sowie unter Einsatz menschlicher Bewerter.
Scientific papers from all disciplines contain many abbreviations and acronyms. In many cases these acronyms are ambiguous. We present a method to choose the contextual correct definition of an acronym that does not require training for each acronym and thus can be applied to a large number of different acronyms with only few instances. We constructed a set of 19,954 examples of 4,365 ambiguous acronyms from image captions in scientific papers along with their contextually correct definition from different domains. We learn word embeddings for all words in the corpus and compare the averaged context vector of the words in the expansion of an acronym with the weighted average vector of the words in the context of the acronym. We show that this method clearly outperforms (classical) cosine similarity. Furthermore, we show that word embeddings learned from a 1 billion word corpus of scientific exts outperform word embeddings learned from much larger general corpora.
Against the background of climate change and finite fossil resources, bio-based plastics have been in the focus of research for the last decade and were identified as a promising alternative to fossil-based plastics. Now, with an evolving bio-based plastic market and application range, the environmental advantages of bio-based plastic have come to the fore and identified as crucial by different stakeholders. While the majority of assessments for bio-based plastics are carried out based on attributional life cycle assessment, there have been only few consequential studies done in this area. Also, the application of eco-design strategies has not been in the focus for the bio-based products due to the prevailing misconceptions of renewable materials (as feedstock for bio-based plastics) considered in itself as an ‘eco-design strategy’. In this paper, we discuss the life cycle assessment as well as eco-design strategies of a bio-based product taking attributional as well as consequential approaches into account.
The reuse of scientific raw data is a key demand of Open Science. In the project NOA we foster reuse of scientific images by collecting and uploading them to Wikimedia Commons. In this paper we present a text-based annotation method that proposes Wikipedia categories for open access images. The assigned categories can be used for image retrieval or to upload images to Wikimedia Commons. The annotation basically consists of two phases: extracting salient keywords and mapping these keywords to categories. The results are evaluated on a small record of open access images that were manually annotated.
Beitrag zum Workshop "Informationskompetenz im Norden" am 01.02.2018 im Bibliotheks- und Informationssytem der Carl von Ossietzky Universität Oldenburg.
Es geht zunächst darum, welche Ansätze und Projekte die Schreibwerkstatt verfolgt, um Informations- & Schreibprozesse an der Hochschule Hannover zu fördern.
Da es gemeinsame Ziele und Zielgruppen von sowie inhaltliche Überschneidungen zwischen Bibliothek und Schreibwerkstatt gibt, werden Kooperationsbeispiele und Vorteile der Zusammenarbeit vorgestellt.
NOA is a search engine for scientific images from open access publications based on full text indexing of all text referring to the images and filtering for disciplines and image type. Images will be annotated with Wikipedia categories for better discoverability and for uploading to WikiCommons. Currently we have indexed approximately 2,7 Million images from over 710 000 scientific papers from all fields of science.