@misc{Ładyżyński_Piotr._Autor_Automatic_2013,
 author={Ładyżyński, Piotr. Autor and Grzegorzewski, Przemysław Wojciech. Autor},
 copyright={Creative Commons Attribution BY 4.0 license},
 address={Warszawa},
 journal={Raport Badawczy = Research Report},
 howpublished={online},
 year={2013},
 publisher={Instytut Badań Systemowych. Polska Akademia Nauk},
 publisher={Systems Research Institute. Polish Academy of Sciences},
 language={eng},
 abstract={As e-commerce is becoming more and more popular, the number of different products reviews done by customer grows rapidly. The efficient method for automatic summarization of customers’ reviews is required. The majority of existing approaches classify a review only whether the opinion is positive or negative. In the present paper we show how to extract product features from the set of the reviews to design feature based summaries of available opinions. These summaries are later used to recommend a customer the best product corresponding to his individual demands.},
 title={Automatic recommendations based on customers’ reviews mining},
 type={Text},
 keywords={Information retrival, Podobieństwo, Wydobywanie informacji, Decision making, Podejmowanie decyzji, If-sets, Recommender system, System rekomendujący, Bipolarity, Opinion mining, Similarity, Text processing, Dwubiegunowość, Eksploracja opinii, Przetwarzanie tekstu},
}