This paper gives a perspective about how Google Maps, one of the world's most influential application works. Google Maps was initially coded in C++ programming language by its founders-Lars and Jens Eilstrup Rasmussen. Formerly it was named 'Where 2 Technologies', which was later acquired by Google Inc. in 2004, which renamed this web-application to Google Maps. Earlier it had limited features restricted to navigation, but today it provides overwhelming features like street-view, ETA and other such intriguing features. It gives an overview about the algorithms and procedures employed by Google Maps to carry out analysis and enable users to carry out desired operations. Various features provided by Google Maps are portrayed in this paper. It describes the algorithms and procedures used by Google Maps to find the shortest path, locate one's position, geocoding and other such elegant features it provides its users.
The casual conversational style used by the students on any front stage environment can educate extensively about their learning process. The collection of data from such an open environment can bring out many important and unknown factors about students" behaviour, their opinions, their feelings their concerns pertaining to their educational system. The inspection of such data can be said to be very provocative. The reflection of students" feelings over the social network, however, has to undergo the human eye to get properly interpreted, which is possible but upto a certain extent, as a result of ever-growing data. In this paper, problems of engineering students have been considered. This has been worked upon by analysing engineering students" tweets from the hashtag #enggproblems on Twitter. Analysis was carried out over 15,000 tweets. These problems were related to heavy study load, negative emotions, sleep problems, lack of social engagement, diversity issues etc. A multi-label classifier was executed to classify and categorize tweets. This technique can dig up into the casual conversations of students and educate about the factors that affect the learning process of students. General TermsMulti-label classification using naïve bayes classifier.
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