This research shows the authorship attribution for three Bengali writers using both Naïve Bayes method and a new method proposed by us which performs better than Naïve Bayes for authorship attribution. Though a lot of works exist in the field of authorship attribution for other languages (especially English); the amount of work in this field for Bengali language is very low. For this experiment, we make our own dataset having 107380 words and 21198 unique words. For both methods, we pre-process our dataset to be compatible to work with the method experiments. For our dataset, Naïve Bayes gives an accuracy of 86% while our method gives an accuracy of 95%. The main inspiration behind our method is that every author has a nature to write some adjacent words and some single words repeatedly.

A large number of people of a country uses public transport for their daily commute. Public transport users in a developed country get many facilities which is absent in a developing country like frequent transport, less traffic jam, maintaining time schedule, etc. In most of the developing countries, intercity public transports do not have any time schedule to arrive and leave in a stoppage and as a result, a person cannot manage his time accordingly which leads to waste valuable time. In this paper, we have proposed a system which is simple, cost-effective and will be able to save time for a public transport user that might be wasted due to bad timing. The system includes vehicle tracking system to trace the location of the transport and a website for the graphical view of the transport locations. A website has been developed with some dummy data to illustrate the proposed idea.