Search for dissertations about: "Random Indexing"
Showing result 1 - 5 of 10 swedish dissertations containing the words Random Indexing.
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1. Extracting Clinical Findings from Swedish Health Record Text
Abstract : Information contained in the free text of health records is useful for the immediate care of patients as well as for medical knowledge creation. Advances in clinical language processing have made it possible to automatically extract this information, but most research has, until recently, been conducted on clinical text written in English. READ MORE
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2. Resource Lean and Portable Automatic Text Summarization
Abstract : Today, with digitally stored information available in abundance, even for many minor languages, this information must by some means be filtered and extracted in order to avoid drowning in it. Automatic summarization is one such technique, where a computer summarizes a longer text to a shorter non-rendundant form. READ MORE
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3. Semantic Spaces of Clinical Text : Leveraging Distributional Semantics for Natural Language Processing of Electronic Health Records
Abstract : The large amounts of clinical data generated by electronic health record systems are an underutilized resource, which, if tapped, has enormous potential to improve health care. Since the majority of this data is in the form of unstructured text, which is challenging to analyze computationally, there is a need for sophisticated clinical language processing methods. READ MORE
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4. Towards Low-Complexity Vector Quantization
Abstract : This thesis is about constructing low-complexity, yet high-performance, vector quantizers (VQs) for 'real-world' sources. Knowledge concerning the source is extracted from a finite training set. In contrast with conventional VQ design procedures, we use the training set to estimate a statistical model for the source. READ MORE
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5. Graph Algorithms for Large-Scale and Dynamic Natural Language Processing
Abstract : In Natural Language Processing, researchers design and develop algorithms to enable machines to understand and analyze human language. These algorithms benefit multiple downstream applications including sentiment analysis, automatic translation, automatic question answering, and text summarization. READ MORE