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- W2402008399 abstract "MONGOOSE is a strategy which separates client assessments that are executing this method for web shopping webpage gives data about best items in all fields like dresses,mobiles,jewellery and blessing articles based upon client rating and conclusion. It is relies on upon the client assessment to include or evacuate the items in our Website. In this data is accumulated for nothing and open sources on the web as often as possible integrated.This is a methodology that looks to lessen the time spends on making a steady information. It lessens an ideal opportunity to-effect of cutting edge investigation administration arrangements. Consumers are often forced to wade through an alarming number of online reviews in order to make an informed product choice .This paper introduces opinion extraction, an unsupervised information-extraction system that mines product reviews in order to build a model of important product features, their evaluation by reviewers, and their relative quality across different product instances. When compared to previous work, it achieves 22% higher precision (at the cost of 3% lower recall) on feature extraction. In addition, it reports an 8% improvement in accuracy on the task of determining whether an opinion sentence is positive or negative. OPINE’s success comes from a more comprehensive effort to identify product features, which enables it to augment review opinions with background information extracted from the Web." @default.
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- W2402008399 date "2016-05-17" @default.
- W2402008399 modified "2023-10-01" @default.
- W2402008399 title "MONGOOSE-Monitoring Global Online Opinions via Semantic Extraction" @default.
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- W2402008399 doi "https://doi.org/10.5120/ijca2016909638" @default.
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