We use many search engines on the Internet in our daily lives. However, they are not perfect. Their scoring function may not model our intent or they may accept only text queries even though we want to carry out a similar image search. In such cases, we need to make a compromise: We continue to use the unsatisfactory service or leave the service. Recently, a new solution, user-side search systems, has been proposed. In this framework, each user builds their own search system that meets their preference with a user-defined scoring function and user-defined interface. Although the concept is appealing, it is still not clear if this approach is feasible in practice. In this demonstration, we show the first fully user-side image search system, CLEAR, which realizes a similar-image search engine for Flickr. The challenge is that Flickr does not provide an official similar image search engine or corresponding API. Nevertheless, CLEAR realizes it fully on a user-side. CLEAR does not use a backend server at all nor store any images or build search indices. It is in contrast to traditional search algorithms that require preparing a backend server and building a search index. Therefore, each user can easily deploy their own CLEAR engine, and the resulting service is custom-made and privacy-preserving. The online demo is available at https://clear.joisino.net. The source code is available at https://github.com/joisino/clear.
翻译:在我们的日常生活中,我们在互联网上使用许多搜索引擎。 然而,这些搜索引擎并不完美。 他们的评分功能可能无法模拟我们的意图, 也可能只是接受文本查询, 尽管我们想要进行类似的图像搜索。 在这样的情况下, 我们需要做出妥协: 我们继续使用不满意的服务或退出服务。 最近, 提出了一个新的解决方案, 用户侧搜索系统。 在此框架中, 每个用户都建立自己的搜索系统, 满足他们喜欢的用户定义的评分功能和用户定义的界面。 虽然这个概念很吸引人, 但这个方法在实践中是否可行还不清楚。 在此演示中, 我们展示第一个用户侧图像搜索系统, 即CLEAR,, 实现Flickr 的类似图像搜索引擎或相应的 API 。 然而, CLEAR在用户侧面上完全意识到它。 CLEAR不使用后端服务器, 也不存储任何图像或建立搜索索引。 与需要准备后端服务器和构建搜索索引的传统搜索算法相悖。 因此, 每一个用户的服务器都可以在网络上使用。 IMFCAR 。 。 因此, 每个用户的搜索引擎可以使用。 。 。 将产生 。 。