Абстрактный

Three Level Feature Extraction for Sentiment Classification

G.Angulakshmi , Dr.R.Manicka Chezian

Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to all human activities and key influencers of our behaviors. Product reviews written by on-line shoppers is a valuable source of information for potential new customers who desire to make an informed purchase decision. Identifying domain-dependent opinion words is a key problem in opinion mining. In this paper, the feature-based opinion mining model has been discussed. In many such cases, these nouns are not subjective but objective. The involved sentences are also objective and imply positive or negative opinions. Thus, this paper discuss about how reviews could be classified using naive bayes algorithm to produce effective result.

Отказ от ответственности: Этот реферат был переведен с помощью инструментов искусственного интеллекта и еще не прошел проверку или верификацию

Индексировано в

Индекс Коперника
Академические ключи
CiteFactor
Космос ЕСЛИ
РефСик
Университет Хамдарда
Всемирный каталог научных журналов
Импакт-фактор Международного инновационного журнала (IIJIF)
Международный институт организованных исследований (I2OR)
Cosmos

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