Efficient air quality sensing serves as one of the essential services provided in any recent smart city. Mostly facilitated by sparsely deployed Air Quality Monitoring Stations (AQMSs) that are difficult to install and maintain, the overall spatial variation heavily impacts air quality monitoring for locations far enough from these pre-deployed public infrastructures. To mitigate this, we in this paper propose a framework named AQuaMoHo that can annotate data obtained from a low-cost thermo-hygrometer (as the sole physical sensing device) with the AQI labels, with the help of additional publicly crawled Spatio-temporal information of that locality. At its core, AQuaMoHo exploits the temporal patterns from a set of readily available spatial features using an LSTM-based model and further enhances the overall quality of the annotation using temporal attention. From a thorough study of two different cities, we observe that AQuaMoHo can significantly help annotate the air quality data on a personal scale.

Success of groups in Meetup is of utmost importance for members who organize them. However, measures of group success in Meetup is quite vague till now. In this paper, we take a step to quantify the success of Meetup groups. Driven by a comprehensive study of our Meetup dataset, we handpick a set of key properties which can potentially regulate a group's success. Finally, we develop a machine learning model leveraging on these features which can predict success of Meetup groups early with high accuracy.

Travel marketers are sitting on a "powerhouse" of data that's has unlimited potential for their consumers – but remains impossible for humans to disseminate, the marketing lead at IBM Asia-Pacific has said. Speaking ahead of her talk at the inaugural Mumbrella Asia Travel Marketing Summit, Chaitali Pramanik said artificial intelligence will help marketers "crack the code" on one of the industry's biggest problems, which is an avalanche of online and offline data. Pramanik, who leads marketing for IBM's AI platform Watson, said while AI has already "transformed the entire landscape" of the travel industry, there is still great potential to further personalise experiences for budding holidaymakers. She said: "Think about the powerhouse of information that's sat in your call centres. It will always say your call may be recorded for training purposes, but how many companies really do that? How many do research to figure out what your customer is saying? That is very powerful information. If we as marketers are able to derive that information and drive results, we can extend improved results and services."