论文标题
语义关系影响基于查询扩展的检索系统的评估
Evaluation of semantic relations impact in query expansion-based retrieval systems
论文作者
论文摘要
随着能够在不同情况下运行的智能系统的需求不断增长（例如，移动中的用户）对用户对此类系统的正确解释对于为用户问题提供一致的答案至关重要。解决此类任务的最有效应用是在自然语言处理和术语语义扩展领域中。这些技术旨在估算输入查询将其重新定义为目的的目标，通常依赖于构建的文本资源来利用不同的语义关系，例如\ emph {synonymy}，\ emph {antonymy}等。本文的目的是使用给定分类法作为信息来源来生成此类资源。所获得的资源被整合到普通的分类器中，以重新设计一组输入查询作为意图并跟踪每个关系的效果，以量化每个语义关系对分类的影响。为此，评估了将这种关系结合时改进和噪声引入之间的最佳权衡。该评估是通过产生资源及其组合的评估，并将其用于调整分类器，该分类器用于将用户问题重新制定为标签。该评估采用广泛而多样化的分类法作为用例，利用其标签作为语义扩展的基础，并生产多个语料库，目的是增强伪Queries估算。
With the increasing demand of intelligent systems capable of operating in different contexts (e.g. users on the move) the correct interpretation of the user-need by such systems has become crucial to give consistent answers to the user questions. The most effective applications addressing such task are in the fields of natural language processing and semantic expansion of terms. These techniques are aimed at estimating the goal of an input query reformulating it as an intent, commonly relying on textual resources built exploiting different semantic relations like \emph{synonymy}, \emph{antonymy} and many others. The aim of this paper is to generate such resources using the labels of a given taxonomy as source of information. The obtained resources are integrated into a plain classifier for reformulating a set of input queries as intents and tracking the effect of each relation, in order to quantify the impact of each semantic relation on the classification. As an extension to this, the best tradeoff between improvement and noise introduction when combining such relations is evaluated. The assessment is made generating the resources and their combinations and using them for tuning the classifier which is used to reformulate the user questions as labels. The evaluation employs a wide and varied taxonomy as a use-case, exploiting its labels as basis for the semantic expansion and producing several corpora with the purpose of enhancing the pseudo-queries estimation.
