Data Mining Mobile Devices (Hardcover)

Jesus Mena

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商品描述

With today’s consumers spending more time on their mobiles than on their PCs, new methods of empirical stochastic modeling have emerged that can provide marketers with detailed information about the products, content, and services their customers desire.

Data Mining Mobile Devices defines the collection of machine-sensed environmental data pertaining to human social behavior. It explains how the integration of data mining and machine learning can enable the modeling of conversation context, proximity sensing, and geospatial location throughout large communities of mobile users.

  • Examines the construction and leveraging of mobile sites
  • Describes how to use mobile apps to gather key data about consumers’ behavior and preferences
  • Discusses mobile mobs, which can be differentiated as distinct marketplaces—including Apple®, Google®, Facebook®, Amazon®, and Twitter®
  • Provides detailed coverage of mobile analytics via clustering, text, and classification AI software and techniques

Mobile devices serve as detailed diaries of a person, continuously and intimately broadcasting where, how, when, and what products, services, and content your consumers desire. The future is mobile—data mining starts and stops in consumers' pockets.

Describing how to analyze Wi-Fi and GPS data from websites and apps, the book explains how to model mined data through the use of artificial intelligence software. It also discusses the monetization of mobile devices’ desires and preferences that can lead to the triangulated marketing of content, products, or services to billions of consumers—in a relevant, anonymous, and personal manner.

商品描述(中文翻譯)

隨著現今消費者在手機上花費的時間超過在個人電腦上的時間,出現了新的經驗性隨機建模方法,可以為行銷人員提供有關消費者對產品、內容和服務的詳細信息。

《挖掘移動設備數據》定義了與人類社交行為相關的機器感知環境數據的收集。它解釋了如何通過數據挖掘和機器學習的結合,實現對大型移動用戶社群中的對話上下文、接近感知和地理空間位置的建模。

- 檢視移動網站的建立和利用
- 描述如何使用移動應用程序收集有關消費者行為和偏好的關鍵數據
- 討論移動市場的不同市場,包括蘋果、谷歌、Facebook、亞馬遜和Twitter
- 提供關於通過聚類、文本和分類人工智能軟件和技術進行移動分析的詳細介紹

移動設備是一個人的詳細日記,不斷且密切地廣播著消費者對產品、服務和內容的需求的地點、方式、時間和內容。未來是移動的,數據挖掘始於消費者的口袋。

書中描述了如何分析來自網站和應用程序的Wi-Fi和GPS數據,並通過使用人工智能軟件對挖掘的數據進行建模。它還討論了將移動設備的需求和偏好商品化,以便以相關、匿名和個人化的方式向數十億消費者銷售內容、產品或服務。