PPT-ComfRide - A Smartphone based Comfortable Public Route Recommendation

ComfRide A Smartphone based Comfortable Public Route Recommendation Authors Rohit Verma Surjya Ghosh Mahankali Saketh Niloy Ganguly Bivas Mitra Sandip Chakraborty Indian Institute of Technology. What percent of the time do you enter false information when asked to register Rather not say Ive never falsified information Under 25 of the time 26 50 of the time 51 75 of the time Over 75 of the time Ive never registered with a site Why dont yo Good experience with this system is gained The Recommendation as revised in 1992 has the aim to make it possible for non CEPT countries to participate in this licensing system The appropriate provisions for this are found mainly in the new ANNEX 3 a By Omar Ibarra. We use our smartphones for almost everything!. Our Society as a whole depends too much on our handheld devices.. Average Time Spent On Smartphone. We tend to spend way too much time on our handheld devices that we miss out on a lot of things like:. Whom to ask for reference and letters of recommendation?. They must:. Know you well (e.g., taken for multiple classes, done a directed study with, talk outside of class). Have known you for a prolonged period of time. A Practical Guide for Obtaining Effective References. Need a Recommendation?. This presentation will provide a practical framework for requesting letters of recommendation.. Letters of recommendation are requested for a number of reasons, most notably:. Content-based recommendation. While CF – methods do not require any information about the items,. it might be reasonable to exploit such information; and. recommend fantasy novels to people who liked fantasy novels in the past. Abstract. Recent years have witnessed an increased interest in recommender systems. Despite significant progress in this field, there still remain numerous avenues to explore. Indeed, this paper provides a study of exploiting online travel information for personalized travel package recommendation. A critical challenge along this line is to address the unique characteristics of travel data, which distinguish travel packages from traditional items for recommendation. To that end, in this paper, we first analyze the characteristics of the existing travel packages and develop a tourist-area-season topic (TAST) model. Criteo. Simon . Dollé. RecSys. . FR, . December. 1. st. , . 2015. We buy. Ad spaces. We buy. Ad spaces. We sell. Clicks. We buy. Ad spaces. We sell. Clicks. that convert. We buy. Ad spaces. We sell. . Source: Nielsen . Total Audience Report 3Q15. Absolute Change in # of Viewers P2+/Monthly. -17,056,000. +7,238,000. Computer Video. Smartphone Video. ManetS. Adeela Huma. 02/02/2017. Introduction - MANETs. MANETs- Mobile ad hoc networks . lacks infrastructure and . central . authority to . establish and . facilitate communication . in the . network. Marcel Wokke. M. Noort, J. Wisse, I. . Smeding-Zuurendonk. , D. van Dijke. http://research.meteogroup.com. Route based forecasting. Why route based forecasting?. Requirements. Example forecast. Current developments!. S. OCIAL. N. ETWORKS. Modified from . R. . . Zafarani. , M. A. . Abbasi. , and H. Liu, . Social Networks . Mining: An Introduction. , Cambridge University Press, 2014. . Difficulties of Decision Making. May, 2010. Summary of Changes to Campus IT Services (2-Year Phase-In). Consolidate and simplify IT policies as part of current campus initiatives. Develop new policy language that explicitly covers the definition of remote computing and how devices are secured. Recommendation . in . ECommerce. Amey. . Sane. CMSC-601. May 11. th. . 2011. Use of Agents in . E. Commerce. . Product Search/Identification (. eg. “. Eyes” by . amazon. ). Information Brokering.