Meet BESS满足贝丝

We hear so much about collaborative web-sites, wikis, user-generated content, the vast dialog that is the blogosphere, social media and social bookmarking, online networking, the whole web 2.0 revolution, that it is hard to imagine a time when finding useful information meant simply tapping in a few keywords into a search engine.我们听到这么多的合作网站，维基，用户生成内容，广大对话框这是博客，社会新闻媒体和社会书签，在线联网，整个网络2.0的革命，这是很难想象的时候发现有用的信息意味着简单地利用几个关键字到搜索引擎。 But, I hear you scream, Google still reigns supreme and the vast majority of web users are still doing just that.但是，我听到你尖叫，谷歌仍至高无上和广大网络用户仍这样做。

Yes, you’re probably right, there is still a lot of educating to do, to persuade the average non-techie user, present excepted, of course, that collaborative methods of finding the best, most relevant, most informative, and perhaps even the most entertaining, information is the future.是的，你可能正确，但仍有很多这样的教育，说服的平均非技术人员的用户，目前例外，当然，协作的方法找到最佳，最相关，最翔实，甚至最娱乐，信息就是未来。

Part of the problem lies with the whole notion that beauty, or relevance more precisely, is in the eye of the beholder.问题的部分原因在于整体概念，即美，或相关更确切地说，是在魔眼杀机。 Web-spam aside, who’s to say that the first page of search engine hits is going to be relevant to members of a particular niche.网络垃圾一边，谁说，第一页的搜索引擎安打将是有关成员的特别位置。 Even with specialist search engines for movie buffs, photographers, artists, scientists, musicians, etc, there is still the problem of information overload.即使有专业的搜索引擎的电影爱好者，摄影师，艺术家，科学家，音乐家，等等，仍然有问题的信息超载。 No search engine yet invented provides the perfect answers for everyone, each and every time.没有搜索引擎还没有发明提供了完美的答案，每个人，每个时间。

Now,现在， Roman Shtykh罗马Shtykh and和 Qun Jin群进 of the Networked Information Systems Laboratory at Waseda University, in Japan, have also recognized that a one-size-fits-all to dealing with information overload is not the most effective way of satisfying anyone’s individual information needs.该网络信息系统实验室的早稻田大学，在日本，也认识到， 一个一刀切的处理信息超载是最有效的方式满足人的个人信息的需求。 But, rather than simply griping about the problem, they propose a new a new form of collaborative personalized search that attempts to understand your search.但是，而不是简单地抱怨的问题，他们提出了一种新的一种新形式的合作个性化的搜索，试图了解您的搜寻范围。

They have developed a web information retrieval framework called Better Search and Sharing (BESS) that captures interactions between users and the system.他们已经开发出一种网上信息检索框架，所谓的更好的搜索和共享（贝丝）捕捉用户之间的相互作用和系统。 This can then be used to produce user profile and then tailor results to personal interests dynamically, the same mechanism could be used to co-evaluate documents found valuable within a specific search context by users with similar interests, their subjective index.这可以被用来生产用户配置文件，然后裁缝结果动态个人的利益，同样的机制可以用来共同探讨发现有价值的文件在一个具体的搜寻范围内的用户具有相似的利益，自己的主观指标。

Currently, systems such as目前，系统，如 Swiki (social wiki, （社会的wiki ， Eurekster was unavailable at the time of writing Eurekster无法在撰写 ), ） ， Rollyo , and the和 Google Custom Search Engine谷歌自定义搜索引擎 correspond to the vertical and mostly community-oriented approach to search personalization.对应于纵向和主要社会为导向的方法，搜索的个性化。 They allow communities to create personalized search engines around specific interests, Shtykh and Jin say.他们让社区创造个性化的搜索引擎围绕着具体利益， Shtykh和金说。 However, the advent of collaborative然而，协作的到来 web 2.0 sites Web 2.0网站 that favor the transition of each person’s activities from passive browsing to active participation have changed the search situation radically.这有利于转型的每个人的活动，从被动浏览，积极参与，改变了局势彻底搜索。

BESS is different.贝丝是不同的。 It is a community-oriented system, but has the features of a horizontal search system, like Google personalized search and a vertical search system like Google custom search rolled into one.这是一个面向社区的系统，但功能的查询系统横向一样，谷歌个性化搜索和垂直搜索系统像谷歌定制搜索合而为一。 “It performs searches on the information assets of both horizontal (the objective index unedited, non-controlled) and vertical (subjective index, evaluated, commented). “它执行搜索信息资产的横向（客观指数跳跃，非控制）和纵向（主观指标，评价，评论） 。

The notion of the subjective index in our research is similar to the “social search” of the vertical community-oriented systems presented above, but differ in the higher degree of personalization for every user, the high granularity of the vertical search model and, finally, the way of collecting and (re-)evaluating the information pieces. 这一概念的主观指数在我们的研究类似的“社会搜索”垂直面向社区的上述系统，但不同程度较高的个性化的每个用户，高粒度的垂直搜索模式，并最终的方式，收集和（重新）评估资料片。

In other words, groups of users are formed dynamically without user intervention, based on matching interests and expertise.换句话说，用户群的形成动态无需用户干预的基础上，匹配的利益和专门知识。 The role of the community becomes indispensable for improving search quality and the evolution of the system, in general, the researchers add.的作用，成为社会不可缺少的改善搜索质量和演化的系统，一般而言，研究人员补充。

So, how does BESS work and what does it (she?) do?因此，如何贝丝工作和什么它（她？ ）怎么办？ The proposed system consists of a contribution software component on the client side and the BESS collaborative information retrieval framework on the server side.拟议的系统包括了贡献软件组件在客户端和贝丝的合作框架内信息检索在服务器端。 The user contribution component would be a Firefox browser extension that allowed new elements (html) to be embedded into the search (engine) result pages (SERPs) next to every result.用户贡献的组成部分将是一个Firefox浏览器扩展，使新元素（ HTML ）的将嵌入到搜索（引擎）结果页面（ SERPs ）旁边的每一个结果。

On the server side, BESS will utilize a web proxy, software to analyze user behavior (not for spyware purposes, of course, but to allow the system to function), a profile construction engine.在服务器端，贝丝将利用网络代理软件来分析用户的行为（而不是间谍软件的目的，当然，但允许该系统的功能） ，配置文件建设引擎。 It then captures user search and post-search behavior, analyzes them statistically generates updated profiles and then searches the growing subjective index to find the optimum hits.然后它捕捉用户的搜索和产后的搜索行为，分析它们产生的最新统计资料，然后搜索日益增长的主观索引来查找最佳安打。

The team has demonstrated proof of principle using the example of a search for Mitsubishi air conditioners.该小组已证明的证据使用原则的例子，寻找三菱空调。 They assume that user Annabelle is looking for information on air-conditioning units in Mitsubishi cars.他们认为，用户安娜贝勒正在寻找信息的空调单位，三菱汽车。 She searches for “Mitsubishi air conditioner”.她搜索“三菱空调” 。 Annabelle, however, is unaware that Mitsubishi Electric produces air-conditioning systems for buildings too and is thinking only of her car.安娜贝勒不过，不知道三菱电机生产的空调系统也为建筑物和思想不仅是她的车。

Conventional SERPs will be a mixed bag of reviews, information, and documents about both vehicular and building A/C units.常规SERPs将是一个好坏参半的评语，信息和文件的有关车辆和建设的A / C单位。 BESS, however, knows that Annabelle is keen on her car and has already been searching for information she flagged as interesting in her subjective index covering other option extras in cars.贝丝然而，知道安娜贝勒热衷于和她的车已经搜索信息标记为她在她的有趣的主观指数涵盖其他选择额外的汽车。 So, BESS presents hits on in-car air-conditioners from Mitsubishi instead of its domestic appliances entries.因此，贝丝介绍点击车内空调从三菱不是其国内家电条目。

Annabelle’s friend Carl who is in the same automobile enthusiasts group may subsequently be looking for car A/C units but searching by company name and the phrase air-conditioners too, but BESS, aware of their shared interest will again fire up the car equipment instead of the domestic units.安娜贝勒的朋友卡尔是谁在同一组的汽车爱好者可能随后将寻找汽车的A / C单位，但搜索公司名称和短语空调太多，但贝丝，意识到他们的共同利益，将再次火了汽车设备，而不是国内单位。 The flagging and tagging of positive hits could be automatic (done by BESS) or deliberate on the part of Annabelle and Carl.该标记和标记的积极安打可自动（所做的贝丝） ，或故意对部分安娜贝勒和卡尔。 Either way, BESS learns about their behavior and builds their community profiles accordingly.无论哪种方式，贝丝得知他们的行为并建立其相应的社会概况。

There is a drawback to BESS.有一个缺点贝丝。 “Any web personalization system requires storing and analyzing personal information,” the researchers say, and “this is seen to be a problem by privacy advocates.” They point out that client-side personalization can alleviate some of the privacy concerns but would preclude BESS from working well with a community. “任何网页的个性化系统需要储存和分析的个人信息， ”研究人员说，和“这被认为是一个问题隐私倡导者。 ”他们指出，客户端的个性化可以减轻一些隐私的关注，但排除贝丝从运作良好的社区。 “We have to consider how to ensure users’ privacy, probably by combining the client-side and server-side approaches for storing and processing user-sensitive information,” they conclude. “我们必须考虑如何确保用户的隐私，可能相结合的客户端和服务器端的方法储存和处理用户的敏感信息， ”他们总结道。 However, there are millions of people using the likes of Google custom search and countless web 2.0 sites, so while privacy is a concern, the benefits of a more powerful and useful search system might outweigh such concerns for many users.然而，还有数以百万计的人使用这样的谷歌定制搜索和无数的Web 2.0网站，因此而隐私权是一个令人关切的问题，带来的好处更强大的和有用的搜索系统可能会超过这些问题对许多用户。

Harnessing user contributions and dynamic profiling to better satisfy individual information search needs, in 利用用户的贡献和动态特征，以更好地满足个人的信息搜索的需求， International Journal of Web and Grid Services 国际期刊网络和网格服务 , 2008, vol. 2008年，第二卷。 4, pp 63-79 4 ，页63-79