学年

教科

質問の種類

TOEIC・英語 大学生・専門学校生・社会人

この長文問題の答えと解説をお願いします。

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

回答募集中 回答数: 0
資格 大学生・専門学校生・社会人

どなたか教えて頂けると助かります。

178 さて、ネットワーク図の基本的な読み この際のヘッダ情報に関する問題を解いてみましょう。 復習問題2 宛先のパソコンに向けてパケットが送信されました。 パケットがRT3から この問題はSTEP1-3.3で扱った問題です。 図中の送信元のパソコンから 前に郵送されているときのアドレスを送信元アドレス、 MACアドレス、 送信元MACアドレスをそれぞれ答えてください。 IPアドレス : D MACアドレス : d Fa0/1 RT2 IPアドレス : B MACアドレス: b 送信元 Fa0/2 Fa0/1 IPアドレス: E Fa0/2 MACアドレス e IPアドレス: C MACアドレス:c RT1 IPアドレス: A MACアドレス:a IPアドレス: F MACアドレス: f Fa0/1 RT3 Fa0/2 IPアドレス: G MACアドレス:g IPアドレス : H MACアドレス : h V Fa0/1 RT4 Fa0/2 IPアドレス:1 MACアドレス:i IPアドレス : J MAC アドレス : j ☐ 宛先 例 図 から 先 解答 IPアドレスは送信元から宛先まで常に同じです。 RT3がRT4ヘパケットを転送 する際は、1つのネットワーク内を通るので、MACアドレスが必要になります。 もしもRT3がRT4のFa0/1のMACアドレスを知らない場合は、 ARPを利用して調 べるんでしたね。よって、解答は次の表のようになります。 ■パケットがRT3からRT4に転送されているときのヘッダ内容 解 情 E L3ヘッダ L2ヘッダ 宛先IPアドレス 送信元IPアドレス 宛先MACアドレス 送信元MACアドレス J A g

回答募集中 回答数: 0
1/105