GM-RKB:Annotation Guidelines

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

• See: GM-RKB:Site ToDo, GM-RKB:Publication Page Template, FormattingStyleGuidelines.

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General

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).

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GM-RKB Publication Pages

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

Notes

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 http://scholar.google.com/

• Once you have located the document in the Reference List look for a "Cited By" link (this link may be absent if there are zero-0 references).
• Copy the link and trim it of non-essential suffixes.
  • E.g. http://scholar.google.com/scholar?cites=13713596836351394156&as_sdt=2005&sciodt=0,5&hl=en becomes http://scholar.google.com/scholar?cites=13713596836351394156

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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.

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GM-RKB Concept Page

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

Guidelines

Prototypical pages include

• Information Extraction Task
• Text Classification Task
• Logistic Regression Algorithm
• Gabor Melli, note that this is a GM-RKB Person Page which has its own guideline below.

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GM-RKB REDIRECT Pages

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

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To-Be Added

Annotation Guidelines

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

this

 [[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

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