CIF: Small: A Theoretical Framework for Dynamic Collaborative Online Information Searching

CIF：小型：动态协作在线信息搜索的理论框架

• 批准号: 2008570
• 负责人: Rohit Negi
• 金额: $ 49.69万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2008570&HistoricalAwards=false
• 关键词: CIF; Small; Theoretical; Framework; Dynamic

The Internet today has been transformed from a network providing connectivity, to a massive repository of human and machine knowledge, with information relevant to nearly every aspect of human life stored in some corner. Search engines allow keyword-based search of this knowledge, and while natural language queries are increasingly useful, searching for complex information often requires human thinking (augmented with the capabilities of search engines) to obtain useful search results. Routine problems require individuals to search the Internet for relevant ideas, a task which may be hindered by lack of expertise in the appropriate subject matters. With pervasive online connectivity, there are potentially unlimited ‘experts’ (or just helpers) available online to contribute their knowledge to problems related to their expertise. This project envisions tapping such potential experts (or helpers) to handle a large number of requests for information, leveraging the power of online collaboration. The relevance of this project should be increasingly apparent as the world moves towards a knowledge-based economy where the Internet is used for collaborative work, a significant part of which involves searching for information. The project will train students who will understand and extend the proposed approach. This project proposes a novel theoretical framework to analyze the dynamics of information searching. It includes information searching to handle multiple requests, collaboration of multiple experts from different fields, exploration of the concepts of expertise mismatch with the population of generated requests, and of diversity of expertise to allow faster searches for multi-disciplinary requests. While the issues to be studied bear similarity with multi-class queuing and scheduling, information searching uniquely uses information-theoretic ideas. These research activities require an interesting interplay between the fields of information theory, queuing theory, scheduling, and social network concepts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

今天的互联网已经从提供连接的网络转变为人类和机器知识的巨大存储库，与人类生活的几乎各个方面相关的信息存储在某个角落，搜索引擎允许基于关键字搜索这些知识。自然语言查询越来越有用，搜索复杂的信息通常需要人类思维（通过搜索引擎的功能增强）才能获得有用的搜索结果，个人需要在互联网上搜索相关想法，这项任务可能会因缺乏而受到阻碍。适当主题的专业知识。普遍的在线连接，可能有无限的“专家”（或只是帮助者）可以在线贡献他们的知识来解决与其专业知识相关的问题，该项目设想利用这些潜在的专家（或帮助者）来处理大量的信息请求，随着世界走向知识经济，利用互联网进行协作工作，该项目的相关性应该越来越明显，其中很大一部分涉及信息搜索。谁将理解并扩展所提议的方法。项目提出了一种新颖的理论框架来分析信息搜索的动态，它包括处理多个请求的信息搜索、来自不同领域的多个专家的协作、探索专业知识与生成的请求群体不匹配的概念以及专业知识的多样性。虽然要研究的问题与多类排队和调度相似，但信息搜索独特地使用信息论思想，这些研究活动需要信息论、排队等领域之间的有趣相互作用。理论、调度和社会该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A Theoretical Framework for Information Search using Online Social Networks

使用在线社交网络进行信息搜索的理论框架

• DOI: 10.1109/globecom48099.2022.10001520
• 发表时间: 2022-12
• 期刊: IEEE Globecom
• 作者: Negi, Rohit;Yilmaz, Mustafa
• 通讯作者: Yilmaz, Mustafa