'GIB SIE WIEDER' is a series of two political compositions, dedicated to exceptional 1 performers Garth Knox (viola d'amore) and Rhodri Davies (harp). In this project the central focus is on resonance in both a musical and wider socio-cultural sense. Finding the term closely correlated to the construction of gender, I direct my inner ear to the hidden background noises of the organisation of society. As a woman and composer, I perceive aural patterns of individual and political significance. In this work my aim is to to deconstruct engrained structures of resonance and assumptions of gender, and redefine them from a personal perspective as the basis for a new compositional identity. In this article, I identify my political perspective as an artist, and describe how this affects and stimulates my creative process. I discuss the compositional approach taken in the two compositions making up 'GIB SIE WIEDER' and their public performances in 2014.

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Web data repositories usually contain references to thousands of real-world entities from multiple sources. It is not uncommon that multiple entities share the same label (polysemes) and that distinct label variations are associated with the same entity (synonyms), which frequently leads to ambiguous interpretations. Further, spelling variants, acronyms, abbreviated forms, and misspellings compound to worsen the problem. Solving this problem requires identifying which labels correspond to the same real-world entity, a process known as entity resolution. One approach to solve the entity resolution problem is to associate an authority identifier and a list of variant forms with each entity-a data structure known as an authority file. In this work, we propose a generic framework for implementing a method for generating authority files. Our method uses information from the Web to improve the quality of the authority file and, because of that, is referred to as WER-Web-based Entity Resolution. Our contribution here is threefold: (a) we discuss how to implement the WER framework, which is flexible and easy to adapt to new domains; (b) we run extended experimentation with our WER framework to show that it outperforms selected baselines; and (c) we compare the results of a specialized solution for author name resolution with those produced by the generic WER framework, and show that the WER results remain competitive.1. for each record do: (a) select one or more attributes and use them to compose a query, (b) submit the query to a search engine, and (c) collect the top m documents in the answer set; 2. parse the documents in the answer set and extract (Webinferred) attributes B j such as URLs, titles, texts of the documents, names, and acronyms used to refer to the entities; 3. using the original attributes A i and the Web-inferred attributes B j , cluster the entity records relative to the primary entity e pr , such that each cluster corresponds to a single real-world entity; 4. in each cluster, select an attribute value to be the canonical entity name, and output the respective entry to the authority file.

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Research agencies in several countries evaluate the impact of scientific publications of researcher groups to define their investments, and one of the main used metrics is the quality of the publication venues where their works were published. Several bibliometric indexes have been formulated by measuring the quality of a publication venue. However, given a set of citations extracted, for example, from curricula vitae of a researcher group, to effectively use bibliometric indexes to evaluate their quality it is necessary to identify correctly the publication venue title of each citation. This task is not easy, since there are not unique identifiers for publication venues. Frequently, citations contain abbreviated forms and acronyms, publication venues share similar titles, sometimes they change their titles, divide or merge, creating new ones. Traditional digital libraries deal with this problem by creating Authority Files. In this work, we present a twofold contribution: (i) the creation of a Computer Science publication venue authority file and (ii) the proposal of a method that uses association rules to disambiguate publication venue titles originated from citations. The disambiguator is a supervised learning method that uses the authority file to train a classifier, whose generated model is a set of association rules to identify publication venues. Experiments show that our method obtains better results than three state of art baselines.