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Christian Weber

    An application of text mining
    Gauge theory on nonorientable four-manifolds
    • This thesis generalizes the moduli space of anti-self dual connections on principal bundles over nonorientable manifolds. Focusing on principal Pin4 bundles over a nonorientable base manifold X, we adapt the Hodge star operator for two forms by twisting it with an involution on the Lie algebra, resulting in an involution on the bundle of adjoint valued two forms. A connection is defined as *-ASD if its curvature resides in the (-1)-eigenspace of this generalized star operator. We analyze the moduli space M of *-ASD gauge equivalence classes of connections on P, beginning with a classification theorem for Pin4 bundles over a four-complex. We explore the local behavior of M, calculate its formal dimension, and examine singularities from reducible connections. A natural compactification of M is defined, and we compare M and its compactifications to the ASD moduli space on an SU2 bundle over the orientation cover of X. The thesis concludes with a discussion of the charge one moduli space on real projective space. Additionally, we prove theorems regarding the moduli space over an oriented four-manifold X with a smooth orientation-preserving action of a finite group, establishing criteria for the existence of non-empty fixed sets in the moduli space and conditions to avoid reducible ASD connections through slight equivariant perturbations of the Riemannian metric on X.

      Gauge theory on nonorientable four-manifolds
    • The account visit feedback given by account and product managers of a sales department is collected and saved into a database. Besides the basic structure created by the storage in a database, the feedback is free text which contains a lot of abbreviations and spoken language. The concepts of text mining are used to create an editorial tool with the goal to present the information to the analysts in a way that they are able to aggregate it to useful and meaningful phrases. Principles like text tokenization, lemmatization and categorization are explained. Approaches like Document Clustering, Information Retrieval and Information Extraction are consolidated into a general Text Mining model. A practical implementation of this model, including some code snippets in PHP and MySQL, leads to the implementation of an integrated piece of software

      An application of text mining