A Framework for Data Mining and Knowledge Discovery in Cloud Computing

Birant, Derya; Yıldırım, Pelin

doi:10.1007/978-3-319-31861-5_11

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…The rapid increase in the amount of data has also caused an increase in the amount of non-structural data. As long as it is not processed, data is stored as a meaningless mass in databases, and it becomes difficult for people to discover knowledge [1,2].…”

Section: Introductionmentioning

confidence: 99%

A real-time social network-based knowledge discovery system for decision making

Yüksel

Tan

2018

Automatika

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The increasing amount of data in social networks has complicated data processing and interpretation. Therefore, intelligent decision-support mechanisms that have the ability to automatically extract meaning from data and interpret the opinions of people in real time have become inevitable. In this study, an intelligent multilingual decision support system was implemented, and a new algorithm that employs text mining and sentiment analysis techniques was developed to automatically interpret the opinions of social network users about the places they plan to visit. The system can be used as a baseline for sentiment analysis in social networks and can be adapted to build new systems. In this study, we set our main focus on Turkish language and show the applicability of our approach for other languages through the experiments for English language. The dataset required for the implementation of text mining techniques was created based on the venue recommendations shared on Foursquare social media platform. As a result, a contribution was made to the way the social network users make decisions without reading thousands of recommendations. Our results show that the developed system achieves classification accuracy of 84.49% for Turkish and 95% for English. Finally, the most liked or disliked foods/beverages are correctly identified for 107 out of 128 venues.

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Section: Introductionmentioning

confidence: 99%