2012
DOI: 10.1016/j.jcss.2011.10.007
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Feature-based opinion mining and ranking

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Cited by 195 publications
(98 citation statements)
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“…However, ranking features using only frequency is not enough. Eirinaki et al [17] propose a HAC(High Adjective Count) algorithm, in which the main idea is that nouns referring to more sentiment words are most likely to be actual product feature. On the basis of this idea, the HAC algorithm takes the number of adjectives for a noun to be its opinion score.…”
Section: Related Workmentioning
confidence: 99%
See 2 more Smart Citations
“…However, ranking features using only frequency is not enough. Eirinaki et al [17] propose a HAC(High Adjective Count) algorithm, in which the main idea is that nouns referring to more sentiment words are most likely to be actual product feature. On the basis of this idea, the HAC algorithm takes the number of adjectives for a noun to be its opinion score.…”
Section: Related Workmentioning
confidence: 99%
“…In the context of feature extraction, a noun or noun phrase is more likely to be a feature if it is modified by quite a few adjectives [17]. Similarly, an adjective is more likely to be a sentiment word if it is the modifier of many product features.…”
Section: The Mhits Algorithmmentioning
confidence: 99%
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“…Another feature extraction technique is The High Adjective Count algorithm (HAC) [3]. The main idea behind the algorithm is that the nouns for which reviewers express a lot of opinions are most likely to be the important and distinguishing features than those for which users don't…”
Section: Feature Extraction Using Hac Algorithmmentioning
confidence: 99%
“…Similarly for organizations it is no longer necessary to organize focused groups and conducting surveys in order to become aware about the consumer opinions or reviews related to its product [6]. It is very arduous for a user to quest for a reliable source on order to extract proper sentences, and then read them, summarize them and categorize them into usable forms this whole process requires an automated opinion mining and summarization system [7].…”
Section: Introductionmentioning
confidence: 99%