GM-RKB:Annotation Guidelines

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This page is the current GM-RKB Annotation Guidelines Document.


  1. GM-RKB's intention is for every item mention of a (possible) GM-RKB Page to be annotated (typically not verbs).
  2. There must not be visible wiki annotation [1].
  3. There must be few GM-RKB malformed pages [2]. E.g. HomePage
  4. Defunct URLs should be removed.
  5. Wiki headings with three or more =s must be preceded and followed by an empty line.
  6. Wiki Heading Text must be prefixed and suffixed with a single space (before and after their neighboring =s).

GM-RKB Publication Pages

The Annotation Guidelines are embedded within the GM-RKB Publication Page.


GM-RKB Publication Pages will receive the most near-term time/energy because:

  1. they involve time-consuming text-annotation
  2. they can be edited by a person who has written a paper that cited its references.
  3. they can be edited by a person with access to The Web and skill to copying and entering data into a specific format

The Google Scholar Page can typically be found by searching for the title in

GM-RKB Author Pages

The Annotation Guidelines are embedded within the GM-RKB Person Pages.

GM-RKB Author Pages will receive some near-term time/energy because:

  1. they do not require domain expertise - the main task is to ensure that the listed publication's are in GM-RKB Citation Format.

GM-RKB Concept Page

This sections describes the Annotation Guideline for GM-RKB Concept Pages (←please read this concept page as well).

Prototypical pages include


  1. must not have additional content.
  2. must have a space between the redirect and the destination.

To-Be Added

Annotation Guidelines

 [[2010_UnsupervisedTransferClassificat|We]] refer to this [[learning task|learning problem]]
 as [[unsupervised transfer classification|unsupervised transfer classification]].


 [[Past papers|Past papers]] have assumed that when the [[CTR of a result|CTR of a result]] varies
 based on the [[pattern|pattern]] of [[click|clicks]] in  [[prior position|prior positions]],
 this [[result variation|variation]] is solely [[due|due]] to [[change|changes]] in
 the [[probability of examination|probability of examination]].
 [[2010_MineFleet174AnOverviewofaWidely|This paper]] describes
 the [[MineFleet|MineFleet]] [[distributed mining system|distributed]]
 [[vehicle performance data mining system|vehicle performance data mining system]] designed
 for [[commercial fleet|commercial fleets]].
high-level specific "This"

To this end, we propose a shared subspace learning framework to leverage a secondary source to improve retrieval performance from a primary dataset. This is achieved by learning a shared subspace