User-Adaptive Search and Evaluation for Complex Information-Seeking Tasks

复杂信息搜索任务的用户自适应搜索和评估

• 批准号: LP150100252
• 负责人: Prof Lawrence Cavedon
• 金额: $ 27.44万
• 依托单位: RMIT University
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2016
• 资助国家: 澳大利亚
• 起止时间: 2016-06-30 至 2019-06-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP150100252
• 关键词: User; Adaptive; Search; Evaluation; Complex

This project plans to develop a new evaluation framework to understand and characterise web users and their situation within complex, multi-faceted search tasks, exemplified through job-search. While evaluation of web search engine effectiveness is relatively well understood, measuring information retrieval performance in the context of complex tasks with heterogeneous users is a largely neglected problem. This project plans to mine user-specific characteristics and situations from complex profiles and interaction logs for online information services run by the industry partner, SEEK. The new techniques are intended to redefine understanding of task-oriented search, and have the potential to reinvent the user experience for complex search tasks. This project will transform how practical search systems are measured within complex task scenarios. This will result in substantial economic impact by enabling businesses providing task-based search services to provide more customized offerings. Within the target domain (job search), this greatly enhances a service highly relevant to Australia's productivity.

该项目计划开发一个新的评估框架，以了解和描述网络用户及其在复杂、多方面的搜索任务中的情况，例如求职。虽然网络搜索引擎有效性的评估相对容易理解，但在异构用户的复杂任务背景下测量信息检索性能是一个很大程度上被忽视的问题。该项目计划从行业合作伙伴 SEEK 运营的在线信息服务的复杂配置文件和交互日志中挖掘用户特定的特征和情况。这些新技术旨在重新定义对面向任务的搜索的理解，并有可能重塑复杂搜索任务的用户体验。该项目将改变在复杂任务场景中衡量实用搜索系统的方式。这将使提供基于任务的搜索服务的企业能够提供更多定制的产品，从而产生巨大的经济影响。在目标领域（求职）内，这极大地增强了与澳大利亚生产力高度相关的服务。