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15 語数: 398 語 出題校 法政大 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,” she says. "You might not remember liking things, " but Facebook remembers and (4) it all adds up.", * a 'like': フェイスブック上で個人の好みを表示する機能。 日本語版のフェイスブックでは「いいね!」 と表記される。 2-56 2-57 2-58 36

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数学 大学生・専門学校生・社会人

(1)は解けました😊 (2)と(3)が難しいです、、。 (2)とかは全て正しく読み込めたと仮定する〜から始めたらなんとかいけそうな気するんですけど、そこから手が進まないです、、

12 雑誌を含めて, 全ての書籍に付与されている固有の番号, ISBN (International Standard Book Num- ber) の秘密について考える. 例: ISBN 4910054230772 末尾の「2」は,「チェックディジット」 とよばれるもので, その前の12個の数字列 491005423077が 正しく入力されたかどうか(例えば, バーコードが正しく読み取れたかどうか) を確認するものである. ここで, チェックディジット 「2」は,「491005423077」 から次の規則により定まっている. 1. 先頭位の数字から順番に, 1,3を掛けていく: 4 9 1 005 4 2 3 0 7 7 x1 x3 x1 x3 x1 x3 x1 x3 x1 x3 x1 x3 4 27 1 0 0 15 4 630 7 21 2. 得られた数を加えて, 10で割った余りを求める(法10で評価する): 4+27 + 1 + 15 +4+6+3+7+21 = 4 +7+1+5+4+6+3+7+1=8 (mod 10) 3. 得られた数 「8」 を10から引いて, チェックディジット 「2」を得る. 10-8=2. 但し, 2. で得られた数が0の場合は, チェックディジットを0 とする. (1) あなたの手元にある本の ISBN について, チェックディジットを確認せよ. (2) 本の汚れなどの理由で, バーコード読み取り機が,ある1つの数字を読み違えたとする. この間違 いのままチェックディジットを計算すると, その値は、真の値とは異なることを一般的に論ぜよ. (3) バーコード読み取り機が,隣り合う場所にある数字1組についてそれら2つ値を入れ替えて読み 取ってしまった. この場合は間違いの検知率は100% ではない. その理由を一般的に論ぜよ.

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