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Preparing Legal Documents for NLP Analysis: Improving the Classification of Text Elements by Using Page Features
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Sentiment Independent Topic Detection in Rated Hospital Reviews ...
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Abstract:
We present a simple method to find topics in user reviews that accompany ratings for products or services. Standard topic analysis will perform sub-optimal on such data since the word distributions in the documents are not only determined by the topics but by the sentiment as well. We reduce the influence of the sentiment on the topic selection by adding two explicit topics, representing positive and negative sentiment. We evaluate the proposed method on a set of over 15,000 hospital reviews. We show that the proposed method, Latent Semantic Analysis with explicit word features, finds topics with a much smaller bias for sentiments than other similar methods. ...
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Keyword:
020 Bibliotheks- und Informationswissenschaft; 410 Linguistik
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URL: https://serwiss.bib.hs-hannover.de/2076 https://dx.doi.org/10.25968/opus-2076
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HsH: Estimating Semantic Similarity of Words and Short Phrases with Frequency Normalized Distance Measures ...
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Sentiment Independent Topic Detection in Rated Hospital Reviews
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Detecting Paraphrases of Standard Clause Titles in Insurance Contracts
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Using Word Embeddings for Unsupervised Acronym Disambiguation ...
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Using Word Embeddings for Unsupervised Acronym Disambiguation
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Editorial for the 17th European Networked Knowledge Organization Systems Workshop (NKOS 2017) ...
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