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English Senior High

ๅ‹•ๅ่ฉžใฎๅ•้กŒใงใ™ใ€‚ๆ•™ใˆใฆใใ ใ•ใ„ใ€‚้ †็•ชใ‚‚ใŠ้ก˜ใ„ใ—ใพใ™

3. ๆฌกใฎๆ—ฅๆœฌ่ชžใซๅˆใ†ใ‚ˆใ†ใซใ€ไธ‹ใฎ่ชžๅฅใ‚’ไธฆในใ‹ใˆ, (A)ใ€(B)ใซๅ…ฅใ‚‹ใ‚‚ใฎใฎ็•ชๅทใ‚’็ญ”ใˆใชใ•ใ„ใ€‚ (1) ๅฝผใฏ็ˆถใฎไป•ไบ‹ใ‚’็ถ™ใใคใ‚‚ใ‚ŠใŒใพใฃใŸใใชใ„ใ€‚ He has ( ) (A) of (B) ( over @no โ‘ข intention @taking (2)ไปŠใฏใพใ ๅค•้ฃŸใ‚’้ฃŸในใŸใใชใ„. ) his father's business. ) (A) ( ) ( ) ( ) (B)( )yet. @like @having โ‘ข do โ‘ฃ dinner โ‘ค not โ‘ฅI feel (3)ๆ™‚ใซใฏใ‚„ใ‚ŠใŸใ„ใจๆ€ใ†ใ“ใจใ‚’ๅพŒๅ›žใ—ใซใ™ใ‚‹ใ“ใจใ‚‚ๅฟ…่ฆใ ใ€‚ ้˜ชๅ—ๅคง [็Ÿณๅทปๅฐ‚ไฟฎๅคง] It is sometimes necessary for one to put ( ) ( ) (A)( )( )(B) ) ). @ doโ‘ก doing โ‘ข off @ one โ‘ค to wants what (4) ๅ…„ใฏๅ“็ƒใงใฏใ ใ‚Œใซใ‚‚่ฒ ใ‘ใŸใ“ใจใŒใชใ„ใ“ใจใ‚’่‡ชๆ…ขใ—ใฆใ„ใ‚‹. My brother ( ) ( ) (A) ( @on @beaten himself )( (็ซ‹ๅ‘ฝ้คจๅคงใ€• )(B)( )at ping-pong. [็މๅทๅคงใ€• having โ‘ค been prides not

Resolved Answers: 1
TOEICใƒปEnglish Undergraduate

ใ“ใฎ้•ทๆ–‡ๅ•้กŒใฎ็ญ”ใˆใจ่งฃ่ชฌใ‚’ใŠ้ก˜ใ„ใ—ใพใ™ใ€‚

15 ่ชžๆ•ฐ: 398 ่ชž ๅ‡บ้กŒๆ ก ๆณ•ๆ”ฟๅคง 5 We are already aware that our every move online is tracked and analyzed. But you 2-53 couldn't have known how much Facebook can learn about you from the smallest of social interactions - a 'like'*. (1) Researchers from the University of Cambridge designed (2) a simple machine-learning 2-54 system to predict Facebook users' personal information based solely on which pages they had liked. E "We were completely surprised by the accuracy of the predictions," says Michael 2-55 Kosinski, lead researcher of the project. Kosinski and colleagues built the system by scanning likes for a sample of 58,000 volunteers, and matching them up with other 10 profile details such as age, gender, and relationship status. They also matched up those likes with the results of personality and intelligence tests the volunteers had taken. The team then used their model to make predictions about other volunteers, based solely on their likes. The system can distinguish between the profiles of black and white Facebook users, 15 getting it right 95 percent of the time. It was also 90 percent accurate in separating males and females, Democrats and Republicans. Personality traits like openness and intelligence were also estimated based on likes, and were as accurate in some areas as a standard personality test designed for the task. Mixing what a user likes with many kinds of other data from their real-life activities could improve these predictions even more. 20 Voting records, utility bills and marriage records are already being added to Facebook's database, where they are easier to analyze. Facebook recently partnered with offline data companies, which all collect this kind of information. This move will allow even deeper insights into the behavior of the web users. 25 30 (3) - Sarah Downey, a lawyer and analyst with a privacy technology company, foresees insurers using the information gained by Facebook to help them identify risky customers, and perhaps charge them with higher fees. But there are potential benefits for users, too. Kosinski suggests that Facebook could end up as an online locker for your personal information, releasing your profiles at your command to help you with career planning. Downey says the research is the first solid example of the kinds of insights that can be made through Facebook. "This study is a great example of how the little things you do online show so much about you,โ€ she says. "You might not remember liking things, " but Facebook remembers and (4) it all adds up.", * a 'like': ใƒ•ใ‚งใ‚คใ‚นใƒ–ใƒƒใ‚ฏไธŠใงๅ€‹ไบบใฎๅฅฝใฟใ‚’่กจ็คบใ™ใ‚‹ๆฉŸ่ƒฝใ€‚ ๆ—ฅๆœฌ่ชž็‰ˆใฎใƒ•ใ‚งใ‚คใ‚นใƒ–ใƒƒใ‚ฏใงใฏใ€Œใ„ใ„ใญ!ใ€ ใจ่กจ่จ˜ใ•ใ‚Œใ‚‹ใ€‚ 2-56 2-57 2-58 36

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English Senior High

ใ“ใฎthoughใฃใฆใฉใ†ใ„ใ†ๅฝนๅ‰ฒใ‚’ใ—ใฆใ„ใ‚‹ใ‚“ใงใ™ใ‹๏ผŸ๏ผŸ thoughใ€although ใฃใฆใใฎ็ฏ€ใงใ€œใ ใŒใ€ใจใ„ใ†้€†่ชฌใ‚’่กจใ™ๆŽฅ็ถš่ฉžใ ใจๆ€ใฃใฆใ„ใŸใ‚“ใงใ™ใŒๆ–‡่„ˆใซๅˆใ‚ใชใใฆโ€ฆ

stories as books. She sent her first book to various publishers, but none of them were interested in publishing it. Unlike the publishers, Potter felt certain that the book would be a success, so in 1901, she paid one publisher to print copies of The Tale of Peter Rabbit. Because of costs, this first version was in black and white. The book was quickly sold out, so the publisher decided to publish a color version. This became a bestseller, and the publisher made a lot of money from that book and the other 22 books written later. Potter's sense of business, though was shown in the way she created and sold goods related to the books. After publishing the first book, she made a doll of Peter Rabbit and patented* it. This was the first time a character from a book had been patented. She then went on to develop dolls, games, dishes, and other products. Today, we are used to seeing toys and products connected with characters from books for sale. Peter Rabbit, though, was the first of these. The methods Potter developed to make a successful business out of her children's books are the ones that are often used by entertainment businesses today.

Unresolved Answers: 1