ASHISH SURESH AWATE
@svkm-iot.ac.in
ASSISTANT PROFESSOR, COMPUTER ENGINEERING
SHRI VILE PARLE KELAVANI MANDAL'S INSTITUTE OF TECHNOLOGY DHULE
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Science
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
Nandwalkar Bhushan, Pardeshi Sukruta, Shahade Makarand, and Awate Ashish
Totem Publisher, Inc.
Ashish S. Awate and Sameer S. Prabhune
IEEE
One of the big surprises of the 21st century has been the ability of all sorts of interesting applications to support themselves through advertising, rather than subscription. While radio and television have managed to use advertising as their primary revenue source, most media, newspapers and magazines had to use a hybrid approach, combining revenue from advertising and subscriptions. By far the most profitable venue for on-line advertising has been search, and much of the effectiveness of search advertising comes from the “adwords” model of matching search queries to advertisements. This paper is to survey of algorithms for optimizing the way this assignment is done. The algorithms used are of an unusual type; they are greedy and they are “on-line” in a particular technical sense to be discussed. This paper discusses these two algorithmic issues - greediness and on-line algorithms - in general, before tackling the adwords problem. A second interesting on-line advertising problem involves selecting items to advertise at an on-line store. This problem involves “collaborative filtering,” where it try to find customers with similar behaviour in order to suggest they buy things that similar customers have bought.