Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation (Hardcover)
暫譯: 加速發現:挖掘非結構化資訊以生成假設 (精裝版)
Scott Spangler
- 出版商: CRC
- 出版日期: 2015-10-09
- 售價: $2,880
- 貴賓價: 9.5 折 $2,736
- 語言: 英文
- 頁數: 292
- 裝訂: Hardcover
- ISBN: 1482239132
- ISBN-13: 9781482239133
-
相關分類:
大數據 Big-data、Data Science
立即出貨 (庫存 < 3)
商品描述
Unstructured Mining Approaches to Solve Complex Scientific Problems
As the volume of scientific data and literature increases exponentially, scientists need more powerful tools and methods to process and synthesize information and to formulate new hypotheses that are most likely to be both true and important. Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation describes a novel approach to scientific research that uses unstructured data analysis as a generative tool for new hypotheses.
The author develops a systematic process for leveraging heterogeneous structured and unstructured data sources, data mining, and computational architectures to make the discovery process faster and more effective. This process accelerates human creativity by allowing scientists and inventors to more readily analyze and comprehend the space of possibilities, compare alternatives, and discover entirely new approaches.
Encompassing systematic and practical perspectives, the book provides the necessary motivation and strategies as well as a heterogeneous set of comprehensive, illustrative examples. It reveals the importance of heterogeneous data analytics in aiding scientific discoveries and furthers data science as a discipline.
商品描述(中文翻譯)
《非結構化資料挖掘方法解決複雜科學問題》
隨著科學數據和文獻的數量以指數級增長,科學家需要更強大的工具和方法來處理和綜合信息,並提出最有可能既真實又重要的新假設。《加速發現:挖掘非結構化信息以生成假設》描述了一種新穎的科學研究方法,利用非結構化數據分析作為生成新假設的工具。
作者開發了一個系統化的過程,利用異質的結構化和非結構化數據來源、數據挖掘和計算架構,使發現過程更快且更有效。這一過程通過讓科學家和發明者更容易分析和理解可能性空間、比較替代方案以及發現全新的方法,來加速人類的創造力。
本書涵蓋系統性和實用性的視角,提供必要的動機和策略,以及一組異質的綜合性、示範性範例。它揭示了異質數據分析在促進科學發現中的重要性,並推進了數據科學作為一門學科的發展。