Abstract
Simple representations of documents based on the occurrences of terms are ubiquitous in areas like Information Retrieval, and also frequent in Natural Language Processing. In this work we propose a logical-probabilistic approach to the analysis of natural language text based in the concept of Uncertain Conditional, on top of a formulation of lexical measurements inspired in the theoretical concept of ideal quantum measurements. The proposed concept can be used for generating topic-specific representations of text, aiming to match in a simple way the perception of a user with a pre-established idea of what the usage of terms in the text should be. A simple example is developed with two versions of a text in two languages, showing how regularities in the use of terms are detected and easily represented.
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Huertas-Rosero, A.F., van Rijsbergen, C.J. (2011). Quantum-Like Uncertain Conditionals for Text Analysis. In: Song, D., Melucci, M., Frommholz, I., Zhang, P., Wang, L., Arafat, S. (eds) Quantum Interaction. QI 2011. Lecture Notes in Computer Science, vol 7052. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24971-6_14
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DOI: https://doi.org/10.1007/978-3-642-24971-6_14
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