环境智能中的多年生、排列和普遍搜索

Javed Mostafa, Xiaopeng Lu, Sandeep Avula
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引用次数: 0

摘要

在环境智能中搜索是复杂的,因为它需要对人类意图进行细粒度跟踪,适应不同的兴趣和意图,并在内容快速变化和信息多样性增加的背景下保持搜索准确性。本文从三个层面描述了一些计算挑战的细节:1)人类与机器的交互,2)一小群人类和机器的协作,以及3)基于大型用户和机器社区背景下多样化和快速发展的信息的决策支持。在讨论这些挑战的同时,还讨论了一些潜在解决方案的初步设想。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Perennial, Permuted, and Pervasive Search in Ambient Intelligence
Searching in ambient intelligence is complex be- cause it requires fine-grained tracking of human intentions, adapting to varying interests and intentions, and maintaining search accuracy in the context of fast content changes and increasing diversity of information. The paper describes details on some of the computational challenges by framing them at three levels: 1) a human interacting with a machine, 2) a small group of humans and machines collaborating, and 3) decision- support based on diverse and fast evolving information in the context of a large community of users and machines. Along with the challenges, some early glimpses of potential solutions are also discussed.
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