Improving aspect-level sentiment analysis with aspect extraction
نویسندگان
چکیده
منابع مشابه
Sentiment Analysis using Aspect Level Classification
The natural language text is analyzed by using sentiment analysis and classified into positive, negative or neutral based on the human emotions, sentiments, opinions expressed in the text. The user reviews and comments on movies on the web are increasing day by day. And to make a decision in movie planning, these reviews are useful for other users. To perform manual analysis of a huge number of...
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This paper presents a pioneering research on aspect-level sentiment analysis in Czech. The main contribution of the paper is the newly created Czech aspectlevel sentiment corpus, based on data from restaurant reviews. We annotated the corpus with two variants of aspect-level sentiment – aspect terms and aspect categories. The corpus consists of 1,244 sentences and 1,824 annotated aspects and is...
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Sentiment analysis or Opinion mining is becoming an important task both from academics and commercial standpoint. In recent years text mining has become most promising area for research. There is an exponential growth with respect to World Wide Web, Mobile Technologies, Internet usage and business on electronic commerce applications. Because of which web opinion sources like online shopping por...
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The LT3 system perceives ABSA as a task consisting of three main subtasks, which have to be tackled incrementally, namely aspect term extraction, classification and polarity classification. For the first two steps, we see that employing a hybrid terminology extraction system leads to promising results, especially when it comes to recall. For the polarity classification, we show that it is possi...
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ژورنال
عنوان ژورنال: Neural Computing and Applications
سال: 2020
ISSN: 0941-0643,1433-3058
DOI: 10.1007/s00521-020-05287-7