¥179,928
  • 参考価格: ¥184,034
  • OFF: ¥4,106 (2%)
  • ポイント: 1799pt (1%)
  • (プライム会員になるとさらに3599pt獲得) プライムに登録
通常配送無料 詳細
ただいま予約受付中です。 在庫状況について
この商品は、Amazon.co.jp が販売、発送します。
裏表紙を表示 表紙を表示
サンプルを聴く 再生中... 一時停止   Audible オーディオエディションのサンプルをお聴きいただいています。
この画像を表示

Encyclopedia of Big Data (英語) ハードカバー – 2022/3/8


その他(2)の形式およびエディションを表示する 他のフォーマットおよびエディションを非表示にする
価格
新品 中古品
ハードカバー ¥119,417
ハードカバー, 2022/3/8
¥179,928
¥179,928
「予約商品の価格保証」対象商品。 詳細
この商品の特別キャンペーン プライム会員限定 最大5%ポイント還元中。 1 件
  • プライム会員限定 最大5%ポイント還元中。
    プライム会員限定最大5%ポイント還元 まとめて買うと最大15%ポイント還元。 特設ページはこちら 販売元: Amazon.co.jp。 詳細はこちら (細則もこちらからご覧いただけます)


ブックマイレージカード
click to open popover

キャンペーンおよび追加情報

  • プライム会員限定最大5%ポイント還元 まとめて買うと最大15%ポイント還元。 特設ページはこちら 販売元: Amazon.co.jp。 詳細はこちら (細則もこちらからご覧いただけます)
  • 「予約商品の価格保証」では、お客様が対象商品を予約注文した時点から発送手続きに入る時点、または発売日のいずれか早い時点までの期間中のAmazon.co.jp のサイト上で表示される最低販売価格が、お支払いいただく金額となります。予約商品の価格保証について詳しくはヘルプページをご覧ください。 詳細はこちら (細則もこちらからご覧いただけます)
  • 【判型について】 洋書の主な判型については こちらをご確認ください。

  • 【買取サービス】 Amazonアカウントを使用して簡単お申し込み。売りたいと思った時に、宅配買取もしくは出張買取を選択してご利用いただけます。 今すぐチェック。

Kindle 端末は必要ありません。無料 Kindle アプリのいずれかをダウンロードすると、スマートフォン、タブレットPCで Kindle 本をお読みいただけます。

  • iOSアプリのダウンロードはこちらをクリック
    Apple
  • Androidアプリのダウンロードはこちらをクリック
    Android
  • Amazonアプリストアへはこちらをクリック
    Android

無料アプリを入手するには、Eメールアドレスを入力してください。

kcpAppSendButton


無料で使えるブックカバー
好きなデザインを選んで取り付けよう! 詳しくはこちら。

商品の説明

内容紹介

This encyclopedia will be an essential resource for our times, reflecting the fact that we currently are living in an expanding data-driven world.  Technological advancements and other related trends are contributing to the production of an astoundingly large and exponentially increasing collection of data and information, referred to in popular vernacular as “Big Data.”  Social media and crowdsourcing platforms and various applications ― “apps” ― are producing reams of information from the instantaneous transactions and input of millions and millions of people around the globe. The Internet-of-Things (IoT), which is expected to comprise tens of billions of objects by the end of this decade, is actively sensing real-time intelligence on nearly every aspect of our lives and environment.  The Global Positioning System (GPS) and other location-aware technologies are producing data that is specific down to particular latitude and longitude coordinates and seconds of the day.  Large-scale instruments, such as the Large Hadron Collider (LHC), are collecting massive amounts of data on our planet and even distant corners of the visible universe.  Digitization is being used to convert large collections of documents from print to digital format, giving rise to large archives of unstructured data.  Innovations in technology, in the areas of Cloud and molecular computing, Artificial Intelligence/Machine Learning, and Natural Language Processing (NLP), to name only a few, also are greatly expanding our capacity to store, manage, and process Big Data.  In this context, the Encyclopedia of Big Data is being offered in recognition of a world that is rapidly moving from gigabytes to terabytes to petabytes and beyond.  

While indeed large data sets have long been around and in use in a variety of fields, the era of Big Data in which we now live departs from the past in a number of key respects and with this departure comes a fresh set of challenges and opportunities that cut across and affect multiple sectors and disciplines, and the public at large.  With expanded analytical capacities at hand, Big Data is now being used for scientific inquiry and experimentation in nearly every (if not all) disciplines, from the social sciences to the humanities to the natural sciences, and more.  Moreover, the use of Big Data has been well established beyond the Ivory Tower.  In today’s economy, businesses simply cannot be competitive without engaging Big Data in one way or another in support of operations, management, planning, or simply basic hiring decisions.  In all levels of government, Big Data is being used to engage citizens and to guide policy making in pursuit of the interests of the public and society in general.  Moreover, the changing nature of Big Data also raises new issues and concerns related to, for example, privacy, liability, security, access, and even the veracity of the data itself.

Given the complex issues attending Big Data, there is a real need for a reference book that covers the subject from a multi-disciplinary, cross-sectoral, comprehensive, and international perspective.  The Encyclopedia of Big Data will address this need and will be the first of such reference books to do so. Featuring some 500 entries, from "Access" to "Zillow," the Encyclopedia will serve as a fundamental resource for researchers and students, for decision makers and leaders, and for business analysts and purveyors.  Developed for those in academia, industry, and government, and others with a general interest in Big Data, the encyclopedia will be aimed especially at those involved in its collection, analysis, and use.  Ultimately, the Encyclopedia of Big Data will provide a common platform and language covering the breadth and depth of the topic for different segments, sectors, and disciplines. 

著者について

Laurie A. Schintler is an Associate Professor in the School of Policy, Government, and International Affairs at George Mason University. Dr. Schintler received her Ph.D.in Urban and Regional Planning at the University of Illinois at Champaign-Urbana and is a well-known computational social scientist and expert in the areas of “Big Data,” network analysis, geospatial analysis, science and technology, health and medicine, transportation, and regional science. Dr. Schintler has over 70 peer-reviewed articles, book chapters, and technical reports, as well as a co-edited book entitled New Advances in Transportation and Telecommunications Modeling: Cross-Atlantic Perspectives (2005), and numerous blog posts, invited presentations, and media appearances.  She is also the recipient of a patent for “System and method for analyzing the structure of logical networks” (USPTO: 20100306372, July 2010; S. Gorman, R. Kulkarni, L. Schintler, and R. Stough).  Dr. Schintler has been a Principal or Co-Principal Investigator on a number of grants from various sponsors, including the United States Department of Transportation, National Institutes of Health, Department of Homeland Security, and National Park Service, among others. She is currently an Associate Director of the Center for Study of International Medical Practices and Policies and Director of the Transportation, Policy, Operations, and Logistics Masters program at George Mason University. She teaches courses in advanced analytical methods and Big Data. Laurie Schintler is also a co-founder of the company Fortiusone (Geoiq), a geospatial data intelligence company (acquired by ESRI, Inc.). 

Connie L. McNeely received her Ph.D. from Stanford University in the field of Sociology and is currently Professor in the School of Policy, Government, and International Affairs at George Mason University, where she also serves as Co-Director of the Center for Science and Technology Policy.  Dr. McNeely’s teaching and research address various aspects of science, technology, and innovation, organizational behavior, globalization, public policy, law and governance, social theory, and culture.  She also is Principal Investigator on major research projects examining national and international scientific networks and policy impacts on diversity in the science and technology workforce, and has received recognition for her work emphasizing complex data analytics, systems mapping, and model construction.  Her recent work has included research in the areas of “Big Data” and data science, education, culture and innovation, and health and medical policy, with ongoing projects examining cultural and institutional dynamics and broader matters of inequality and polity participation.  Moreover, in addition to new and forthcoming articles in major journals on “Big Data” and the organization of related symposia, she has been an invited speaker and participant in various workshops and conferences on the topic, and has prepared reports for public and private entities on computational scientists and exascale computing activities.  She also leads a Research Group on Global Innovation in Science and Technology.  Dr. McNeely has numerous publications and is active in several professional associations, serves as a reviewer and evaluator in a variety of programs and venues, and sits on several advisory boards and committees.



登録情報

  • ハードカバー
  • 出版社: Springer; 1st ed. 2022版 (2022/3/8)
  • 言語: 英語
  • ISBN-10: 3319320114
  • ISBN-13: 978-3319320113
  • 発売日: 2022/3/8
  • 商品の寸法: 15.5 x 23.5 cm
  • カスタマーレビュー: この商品の最初のレビューを書き込んでください。
  • さらに安い価格について知らせる

  • 目次を見る

まだカスタマーレビューはありません

星5つ (0%) 0%
星4つ (0%) 0%
星3つ (0%) 0%
星2つ (0%) 0%
星1つ (0%) 0%

この商品をレビュー

他のお客様にも意見を伝えましょう