Google Trends时间序列
Calibration of Google Trends Time Series
摘要：
Google Trends是一个工具，允许研究人员分析Google搜索查询在时间和空间上的流行程度。在一个请求中，用户可以获得最多5个查询的时间序列，这些查询在一个共同的尺度上，标准化为0到100的范围，并四舍五入到整数精度。尽管谷歌趋势的整体价值，四舍五入造成重大问题，在某种程度上，完全没有信息，全零的时间序列可能会返回不受欢迎的查询时，要求与更流行的查询。我们通过提出Google趋势锚库（G-TAB）来解决这个问题，这是一种用于校准Google趋势数据的有效解决方案。我们的方法表达了一个共同的规模上的任意数量的查询，而不会受到舍入误差的流行。该方法分两个阶段进行。在离线预处理阶段，构建一个“锚点库”，这是一组跨越整个流行范围的查询，通过仔细将多个Google Trends请求链接在一起，所有查询都根据公共参考查询进行校准。在在线部署阶段，通过在锚点库中执行有效的二分搜索来校准任何给定的搜索查询。每个搜索步骤都需要一个Google趋势请求，但很少有步骤就足够了，正如我们在实证评估中所展示的那样。我们在https://github.com/epfl-dlab/GoogleTrendsAnchorBank上将我们的代码作为一个易于使用的库公开提供。
英文摘要：
Google Trends is a tool that allows researchers to analyze the popularity of Google search queries across time and space. In a single request, users can obtain time series for up to 5 queries on a common scale, normalized to the range from 0 to 100 and rounded to integer precision. Despite the overall value of Google Trends, rounding causes major problems, to the extent that entirely uninformative, all-zero time series may be returned for unpopular queries when requested together with more popular queries. We address this issue by proposing Google Trends Anchor Bank (G-TAB), an efficient solution for the calibration of Google Trends data. Our method expresses the popularity of an arbitrary number of queries on a common scale without being compromised by rounding errors. The method proceeds in two phases. In the offline preprocessing phase, an "anchor bank" is constructed, a set of queries spanning the full spectrum of popularity, all calibrated against a common reference query by carefully chaining together multiple Google Trends requests. In the online deployment phase, any given search query is calibrated by performing an efficient binary search in the anchor bank. Each search step requires one Google Trends request, but few steps suffice, as we demonstrate in an empirical evaluation. We make our code publicly available as an easy-to-use library at https://github.com/epfl-dlab/GoogleTrendsAnchorBank.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
