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论文阅读1值得借鉴的写作部分:The Docker Hub2 is a Web application that stores and distributes
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1
值得借鉴的写作部分:
The Docker Hub2 is a Web application that stores and distributes Docker images.
It is the most convenient way to find and discover existing docker images. The
Docker Hub is open-source, under the Apache license. As shown in Figure 1 ach
web page of the Docker Hub describes a docker image. It is composed of several
elements: 1) image name: it is usually chosen with care as it is the only item
presented in the Docker Hub List Page. 2) star: The image name is associated with
a star the user can highlight when this image is one of his favorites. 3) date of
publication: the date when the current version of this image has been made
available on the Docker Hub (creation date or update date). 4) short description:
the short description is a small text (less than 100 characters) where the image
provider gives a summary description of the image. The content of this short text
is carefully written by authors as it is the second level contact of potential users,
after the image name. 5) full description: the full description is a larger text where
the image provider describes in details the image, provides links to download and
install the image and gives details on installation parameters like port number as
well as related docker images. 6) links: in the full description, one can find links to
Docker files3: they give the exact location to the docker image files. 7) comments:
a set of elements in the page provide users comments. They can be divided into
several pages, accessible through the page navigation area. Comments are the
collaborative part of the page, where visitors can discuss the image, give their
opinions, propose improvements etc. 8) comment author’s nickname: for each
comment, the nickname of the user who posted the comment is provided. 9) date
of comment publication: for each comment, the date of comment publication is
given. 10) comment contents: user generated content, that contain either opinion
or user experience with the image, that can be very valuable for other users. 11)
docker pull command: the command line that allows to download an image.
2
Use dockerfile to process the tag:
• Use Logistic Regression based method (semi-automatic labeling) to generate the
training data set.
• Abstract the tag recommendation into a multi-label learning problem. A review on
multi-label learning algorithms
The origin of the data set:
Initially crawled 118,427 Docker repositories from Docker Hub.
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