Contextualizing and Expanding Conversational Queries without Supervision

IF 5.4 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Antonios Minas Krasakis, Andrew Yates, Evangelos Kanoulas
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引用次数: 0

Abstract

Most conversational passage retrieval systems try to resolve conversational dependencies by using an intermediate query resolution step. To do so, they synthesize conversational data or assume the availability of large-scale question rewritting datasets. To relax those conditions, we propose a zero-shot unified resolution–retrieval approach, that (i) contextualizes and (ii) expands query embeddings using the conversation history and without fine-tuning on conversational data. Contextualization biases the last user question embeddings towards the conversation. Query expansion is used in two ways: (i) abstractive expansion generates embeddings based on the current question and previous history, whereas (ii) extractive expansion tries to identify history term embeddings based on attention weights from the retriever. Our experiments demonstrate the effectiveness of both contextualization and unified expansion in improving conversational retrieval. Contextualization does so mostly by resolving anaphoras to the conversation and bringing their embeddings closer to the important resolution terms that were omitted. By adding embeddings to the query, expansion targets phenomena of ellipsis more explicitly, with our analysis verifying its effectiveness on identifying and adding important resolutions to the query. By combining contextualization and expansion, we find that our zero-shot unified resolution–retrieval methods are competitive and can even outperform supervised methods.

上下文化和扩展会话查询没有监督
大多数会话通道检索系统试图通过使用中间查询解析步骤来解决会话依赖关系。为此,他们合成会话数据或假设大规模问题重写数据集的可用性。为了放松这些条件,我们提出了一种零采样统一分辨率检索方法,该方法(i)将会话历史上下文化,(ii)使用会话历史扩展查询嵌入,而不需要对会话数据进行微调。语境化使最后的用户问题嵌入偏向于对话。查询扩展以两种方式使用:(i)抽象扩展基于当前问题和以前的历史生成嵌入,而(ii)抽取扩展试图根据检索者的关注权重来识别历史术语嵌入。我们的实验证明了语境化和统一扩展在提高会话检索方面的有效性。语境化主要是通过解决对话中的回指,并使其嵌入更接近被省略的重要解决术语来实现的。通过在查询中添加嵌入,扩展更明确地针对省略号现象,我们的分析验证了它在识别和添加查询重要分辨率方面的有效性。通过将上下文化和扩展相结合,我们发现我们的零射击统一分辨率检索方法具有竞争力,甚至可以优于监督方法。
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来源期刊
ACM Transactions on Information Systems
ACM Transactions on Information Systems 工程技术-计算机:信息系统
CiteScore
9.40
自引率
14.30%
发文量
165
审稿时长
>12 weeks
期刊介绍: The ACM Transactions on Information Systems (TOIS) publishes papers on information retrieval (such as search engines, recommender systems) that contain: new principled information retrieval models or algorithms with sound empirical validation; observational, experimental and/or theoretical studies yielding new insights into information retrieval or information seeking; accounts of applications of existing information retrieval techniques that shed light on the strengths and weaknesses of the techniques; formalization of new information retrieval or information seeking tasks and of methods for evaluating the performance on those tasks; development of content (text, image, speech, video, etc) analysis methods to support information retrieval and information seeking; development of computational models of user information preferences and interaction behaviors; creation and analysis of evaluation methodologies for information retrieval and information seeking; or surveys of existing work that propose a significant synthesis. The information retrieval scope of ACM Transactions on Information Systems (TOIS) appeals to industry practitioners for its wealth of creative ideas, and to academic researchers for its descriptions of their colleagues'' work.
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