来自爱可可的前沿推介

[IR] Taking Search to Task

C Shah, R W. White, P Thomas, B Mitra, S Sarkar, N Belkin
[University of Washington & Microsoft Research & Rutgers University]

关于搜索中任务的综述

要点:

  1. 提供了各种观点，说明 IR 中任务的最新进展，衍生和使用任务信息的瓶颈，以及探索方向；
  2. 综合了理解、提取和解决以任务为重点的搜索的历史和当前观点；
  3. 提出一种新的框架性方法，用类似树状的结构，以实现不同的解释和应用。

一句话总结:
本文阐述了IR中任务的最新进展，衍生和使用任务信息的一些瓶颈，提出一种采用树状结构的任务框架性方法，以帮助重振基于任务的IR的兴趣和未来工作，特别是面向对话智能体和主动IR等新兴领域。

摘要：
长期以来，信息检索(IR)中任务的重要性一直被讨论，以不同的方式处理，经常被忽视，也经常被重新审视。几十年来，学者们证明了用户任务在用户如何以及为什么参与搜索以及搜索系统应该做些什么来提供帮助方面所起的作用。但在大多数情况下，IR社区过于专注于查询处理和假设搜索任务是用户查询的集合，往往忽视这种假设是否或如何帮用户解决任务。随着对话智能体和主动式IR等新领域的出现，理解和解决用户任务比以往任何时候都更加重要。本文提供了各种观点，说明IR中任务的最新进展，衍生和使用任务信息的一些瓶颈是什么，以及如何从这里继续前进。除了涵盖相关文献外，本文还综合了理解、提取和解决以任务为重点的搜索的历史和当前观点。为了奠定该领域正在进行的和未来研究的基础，本文提出了一种新的框架性方法，使用类似树状的结构，以实现不同的解释和应用。本文结合了想法和过去的工作、未来研究的建议以及对技术、社会和伦理考虑的看法，旨在帮助重振基于任务的IR的兴趣和未来工作。

The importance of tasks in information retrieval (IR) has been long argued for, addressed in different ways, often ignored, and frequently revisited. For decades, scholars made a case for the role that a user's task plays in how and why that user engages in search and what a search system should do to assist. But for the most part, the IR community has been too focused on query processing and assuming a search task to be a collection of user queries, often ignoring if or how such an assumption addresses the users accomplishing their tasks. With emerging areas of conversational agents and proactive IR, understanding and addressing users' tasks has become more important than ever before. In this paper, we provide various perspectives on where the state-of-the-art is with regard to tasks in IR, what are some of the bottlenecks in deriving and using task information, and how do we go forward from here. In addition to covering relevant literature, the paper provides a synthesis of historical and current perspectives on understanding, extracting, and addressing task-focused search. To ground ongoing and future research in this area, we present a new framing device for tasks using a tree-like structure and various moves on that structure that allow different interpretations and applications. Presented as a combination of synthesis of ideas and past works, proposals for future research, and our perspectives on technical, social, and ethical considerations, this paper is meant to help revitalize the interest and future work in task-based IR.

https://arxiv.org/abs/2301.05046
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