The clash between the Warriors and Nets ended with the NBA champions getting crushed (113-143).
Already at the halftime there was no doubt which team will the game as Brooklyn led by 40 points.
It was a record-setting halftime deficit for a defending NBA champion, as observed by ESPN Stats & Info on Twitter.
The Warriors' road woes have continued so far tonight in Brooklyn as they trail by 40 at halftime against the Nets.
— ESPN Stats & Info (@ESPNStatsInfo) December 22, 2022
The 40-point margin is the largest halftime deficit by a defending champion in NBA history. pic.twitter.com/qTcTo1oLfI
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An apparel company wishes to promote its new line of high-end baby clothes. It gets in touch with an agency that has a network of clients with high income customers (such as high-end supermarkets) and asks the agency to create profiles of young parents or couples who can be assumed to be wealthy and to have a new child, so that these can later be used to present advertising within partner apps based on those profiles.
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A profile created for personalised advertising in relation to a person having searched for bike accessories on a website can be used to present the relevant advertisement for bike accessories on a mobile app of another organisation.
Information about your activity on this service (for instance, forms you submit, non-advertising content you look at) can be stored and combined with other information about you (such as your previous activity on this service or other websites or apps) or similar users. This is then used to build or improve a profile about you (which might for example include possible interests and personal aspects). Your profile can be used (also later) to present content that appears more relevant based on your possible interests, such as by adapting the order in which content is shown to you, so that it is even easier for you to find content that matches your interests.
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You read several articles on how to build a treehouse on a social media platform. This information might be added to a profile to mark your interest in content related to outdoors as well as do-it-yourself guides (with the objective of allowing the personalisation of content, so that for example you are presented with more blog posts and articles on treehouses and wood cabins in the future).
You have viewed three videos on space exploration across different TV apps. An unrelated news platform with which you have had no contact builds a profile based on that viewing behaviour, marking space exploration as a topic of possible interest for other videos.
Content presented to you on this service can be based on your content personalisation profiles, which can reflect your activity on this or other services (for instance, the forms you submit, content you look at), possible interests and personal aspects. This can for example be used to adapt the order in which content is shown to you, so that it is even easier for you to find (non-advertising) content that matches your interests.
Examples:
You read articles on vegetarian food on a social media platform and then use the cooking app of an unrelated company. The profile built about you on the social media platform will be used to present you vegetarian recipes on the welcome screen of the cooking app.
You have viewed three videos about rowing across different websites. An unrelated video sharing platform will recommend five other videos on rowing that may be of interest to you when you use your TV app, based on a profile built about you when you visited those different websites to watch online videos.
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Examples:
You have clicked on an advertisement about a “black Friday” discount by an online shop on the website of a publisher and purchased a product. Your click will be linked to this purchase. Your interaction and that of other users will be measured to know how many clicks on the ad led to a purchase.
You are one of very few to have clicked on an advertisement about an “international appreciation day” discount by an online gift shop within the app of a publisher. The publisher wants to have reports to understand how often a specific ad placement within the app, and notably the “international appreciation day” ad, has been viewed or clicked by you and other users, in order to help the publisher and its partners (such as agencies) optimise ad placements.
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Examples:
The owner of an online bookstore wants commercial reporting showing the proportion of visitors who consulted and left its site without buying, or consulted and bought the last celebrity autobiography of the month, as well as the average age and the male/female distribution of each category. Data relating to your navigation on its site and to your personal characteristics is then used and combined with other such data to produce these statistics.
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Examples:
A technology platform working with a social media provider notices a growth in mobile app users, and sees based on their profiles that many of them are connecting through mobile connections. It uses a new technology to deliver ads that are formatted for mobile devices and that are low-bandwidth, to improve their performance.
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Content presented to you on this service can be based on limited data, such as the website or app you are using, your non-precise location, your device type, or which content you are (or have been) interacting with (for example, to limit the number of times a video or an article is presented to you).
Examples:
A travel magazine has published an article on its website about the new online courses proposed by a language school, to improve travelling experiences abroad. The school’s blog posts are inserted directly at the bottom of the page, and selected on the basis of your non-precise location (for instance, blog posts explaining the course curriculum for different languages than the language of the country you are situated in).
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