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Measuring performance of metasearch engines to access information: an exploratory study based on precision metrics
Performance Measurement and Metrics Pub Date : 2024-03-18 , DOI: 10.1108/pmm-09-2023-0028
Raj Kumar Bhardwaj , Ritesh Kumar , Mohammad Nazim

Purpose

This paper evaluates the precision of four metasearch engines (MSEs) – DuckDuckGo, Dogpile, Metacrawler and Startpage, to determine which metasearch engine exhibits the highest level of precision and to identify the metasearch engine that is most likely to return the most relevant search results.

Design/methodology/approach

The research is divided into two parts: the first phase involves four queries categorized into two segments (4-Q-2-S), while the second phase includes six queries divided into three segments (6-Q-3-S). These queries vary in complexity, falling into three types: simple, phrase and complex. The precision, average precision and the presence of duplicates across all the evaluated metasearch engines are determined.

Findings

The study clearly demonstrated that Startpage returned the most relevant results and achieved the highest precision (0.98) among the four MSEs. Conversely, DuckDuckGo exhibited consistent performance across both phases of the study.

Research limitations/implications

The study only evaluated four metasearch engines, which may not be representative of all available metasearch engines. Additionally, a limited number of queries were used, which may not be sufficient to generalize the findings to all types of queries.

Practical implications

The findings of this study can be valuable for accreditation agencies in managing duplicates, improving their search capabilities and obtaining more relevant and precise results. These findings can also assist users in selecting the best metasearch engine based on precision rather than interface.

Originality/value

The study is the first of its kind which evaluates the four metasearch engines. No similar study has been conducted in the past to measure the performance of metasearch engines.



中文翻译:

衡量元搜索引擎访问信息的性能:基于精度指标的探索性研究

目的

本文评估了四种元搜索引擎(MSE)——DuckDuckGo、Dogpile、Metacrawler 和 Startpage 的精度,以确定哪个元搜索引擎具有最高的精度水平,并确定最有可能返回最相关搜索结果的元搜索引擎。

设计/方法论/途径

研究分为两部分:第一阶段涉及分为两个部分的四个查询(4-Q-2-S),第二阶段包括分为三个部分的六个查询(6-Q-3-S)。这些查询的复杂程度各不相同,分为三种类型:简单查询、短语查询和复杂查询。确定所有评估的元搜索引擎的精度、平均精度和重复项的存在。

发现

研究清楚地表明,Startpage 返回了最相关的结果,并在四个 MSE 中实现了最高的精度 (0.98)。相反,DuckDuckGo 在研究的两个阶段都表现出一致的表现。

研究局限性/影响

该研究仅评估了四个元搜索引擎,这可能无法代表所有可用的元搜索引擎。此外,使用了有限数量的查询,这可能不足以将结果推广到所有类型的查询。

实际影响

这项研究的结果对于认证机构管理重复、提高搜索能力以及获得更相关和更精确的结果非常有价值。这些发现还可以帮助用户根据精度而不是界面来选择最佳的元搜索引擎。

原创性/价值

该研究是同类研究中第一个评估四种元搜索引擎的研究。过去没有进行过类似的研究来衡量元搜索引擎的性能。

更新日期:2024-03-18
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