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Preface to Special Issue on User Modeling for Web Information Retrieval

机译：Web信息检索用户建模特刊的序言

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Information access is one of the hottest topics of information society and it has become even more important since the advent of the Web. On one side, our society relies more and more on information, both for professional and personal goals. Information is nowadays considered as one of the most valuable and strategic goods: knowing the right information, at the right moment, as soon as it is available is a 'must' for all of us. On the other side, the amount of available information, especially on the Web, is increasing tremendously over time and we are witnessing an 'information oversupply', a phenomenon called in other different, though significant, ways: 'information overload', 'information glut', 'infobog', 'information smog', 'e-overload' (Alesandrini, 1992; Shenk, 1997). As a result, the process of accessing what is 'relevant' is very difficult, time-consuming, and in many cases practically unfeasible, since it requires huge cognitive processing, which is out of range for our limited mental resources, energy, and time. For these reasons, since the very beginning of the Web, several automatic tools, which are aimed at supporting the user in finding information relevant to his/her information needs, have been proposed and are still currently exploited. Search engines, meta-search engines, and directories are the most popular tools, however they show very limited performance. We all know that search engines are characterized by low accuracy of the retrieval process (an estimated average precision of 30% (Leighton and Srivastava, 1999), incompleteness and low coverage, low timeliness, and bad ranking of results. Such results hinder effectiveness and efficiency of the process characterizing the transfer of information from authors (producers of information) to readers (consumers of information). It can be observed both when we are searching for information because of a specific information need (the so called 'pull perspective') or when information is sent to us with or without our permission (the so called 'push perspective').
机译：信息访问是信息社会最热门的主题之一，并且自从Web出现以来，它就变得越来越重要。一方面，我们的社会越来越依赖于信息，无论是职业目标还是个人目标。如今，信息被认为是最有价值和具有战略意义的商品之一：在正确的时间，一旦获得可用的信息就知道正确的信息是我们所有人的“必须”。另一方面，随着时间的推移，可用信息的数量（尤其是在Web上）正在急剧增加，我们正在目睹“信息供过于求”，这种现象以其他不同但重要的方式被称为：“信息超载”，“信息” glut”，“ infobog”，“ information smog”，“ e-overload”（Alesandrini，1992年； Shenk，1997年）。结果，访问“相关”内容的过程非常困难，耗时，并且在许多情况下实际上是不可行的，因为它需要大量的认知处理，这超出了我们有限的智力，精力和时间范围。由于这些原因，自从网络开始以来，已经提出了几种自动工具，这些工具旨在支持用户查找与其信息需求有关的信息。搜索引擎，元搜索引擎和目录是最受欢迎的工具，但是它们的性能却非常有限。我们都知道搜索引擎的特点是检索过程的准确性较低（估计平均准确性为30％（Leighton和Srivastava，1999年），不完整和覆盖率低，时效性差以及结果排名不佳。从作者（信息的生产者）到读者（信息的消费者）的信息传递过程的效率；可以在由于特定信息需求而搜索信息时观察到这两种情况（所谓的“拉动视角”）或在未经我们许可的情况下将信息发送给我们的情况（即所谓的“推动观点”）。

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