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Recently, modern Web search engine have also relied on recommendation techniques to address Web search challenges and to implement advanced search features.
Recommending to groups is clearly more complicated than recommending to individuals. Assuming that we know precisely what is good for individual users, the issue is how to combine individual user models.
Privacy preserving recommender systems. RSs exploit user data to generate personalized recommendations. This will clearly have a negative impact on the privacy of the users and the users may start feeling that the system knows too much about their true preferences.
A man walked into the local Target store in Minneapolis and demanded to speak to the manager. He wanted to know why his then-high school daughter was receiving coupons and promotions for maternity clothing, cribs, and other items that would indicate she was pregnant. “Are you trying to encourage her to get pregnant?” he asked. The store manager examined the stack of coupons and promptly apologized. He said he did not have any idea why the girl had received the coupons.
The man then left for home. This could have been the end of the story. But after talking to his daughter the man discovered she was pregnant.
Target had used sophisticated predictive analytics to determine that her previous buying patterns and behaviour had indicated a high probability of expecting a baby. In fact, Target and other stores have become so good at gauging customers’ buying patterns they now disguise customer-specific promotions by including coupons that are completely irrelevant to the recipient.
?dvertising models designed to maximize results and revenues.
There are clearly advantages to receiving relevant ads, but the Internet, combined with today’s data-collection technology, poses serious privacy concerns. Unfortunately, most consumers feel as though they have little control over what happens to their data and how it is used by advertisers. In many cases, advertisers simply hope for positive results and learn by trial and error.
A growing number of retailers, including Target, assign each customer a unique ID number or guest code.
The result is a fairly comprehensive picture of an individual’s buying habits and consumption patterns. This profile which could include anything from the type of tea or liquor a person likes to consume to medical conditions and sexual orientation allows marketers to customize ads, but it also offers deep insights into life events and changes.
Increasingly, they are including coupons and ads that are completely random or irrelevant in order to appear as though they are not spying over a person’s shoulder.
People like the idea of personalized searches and advertising
What makes the emerging field of data aggregation and analytics possible is a spate of online data-collection techniques that revolve around IP addresses, third-party cookies, and Web tools that track consumers as they click through Web sites and interact online.
It is akin to a company installing video cameras and microphones in a home and recording everything that occurs in the household.
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