CVS update: openprivacy/htdocs/notes/reputations

From: cvs@openprivacy.org
Date: Tue Dec 12 2000 - 18:49:39 PST


Date: Tuesday December 12, 19100 @ 18:49
Author: fen
CVSWEB Options: -------------------

Main CVSWeb: http://openprivacy.org/cgi-bin/cvsweb/cvsweb.cgi

View this module: http://openprivacy.org/cgi-bin/cvsweb/cvsweb.cgi/openprivacy/htdocs/notes/reputations

-----------------------------------

Update of /usr/local/cvsroot/openprivacy/htdocs/notes/reputations
In directory openprivacy.org:/home/fen/projects/openprivacy/htdocs/notes/reputations

Modified Files:
        requirements.txt
Log Message:
updated sorting/ranking section

*****************************************************************
File: openprivacy/htdocs/notes/reputations/requirements.txt

CVSWEB Options: -------------------

CVSWeb: Annotate this file: http://openprivacy.org/cgi-bin/cvsweb/cvsweb.cgi/openprivacy/htdocs/notes/reputations/requirements.txt?annotate=1.21

CVSWeb: View this file: http://openprivacy.org/cgi-bin/cvsweb/cvsweb.cgi/openprivacy/htdocs/notes/reputations/requirements.txt?rev=1.21&content-type=text/x-cvsweb-markup

CVSWeb: Diff to previous version: http://openprivacy.org/cgi-bin/cvsweb/cvsweb.cgi/openprivacy/htdocs/notes/reputations/requirements.txt.diff?r1=1.21&r2=1.20

-----------------------------------

Index: openprivacy/htdocs/notes/reputations/requirements.txt
diff -u openprivacy/htdocs/notes/reputations/requirements.txt:1.20 openprivacy/htdocs/notes/reputations/requirements.txt:1.21
--- openprivacy/htdocs/notes/reputations/requirements.txt:1.20 Tue Dec 12 18:38:48 2000
+++ openprivacy/htdocs/notes/reputations/requirements.txt Tue Dec 12 18:49:39 2000
@@ -1,4 +1,4 @@
-$Id: requirements.txt,v 1.20 2000/12/13 02:38:48 fen Exp $
+$Id: requirements.txt,v 1.21 2000/12/13 02:49:39 fen Exp $
 
 Reputation Server Requirements: top level feature list
 
@@ -101,28 +101,26 @@
 
 D. === sorting, ranking, calculating ===
 
-Sorting, ranking
- results may be returned ranked according to local server rules
- enhance the object with high billing or additional local reputation if:
- the signature/content/object has high reputation
- the price(mojo)/KB, availability, speed, similar content types,
- feature set (e.g. does it support query), etc. meets set levels
-
-Reputation calculation (may require peer communications)
- given an object, return its known reputation components
- as a set of object grafts
- as a merged value (computed via a bias)
- facility for 'blending' reputation results from multiple sources. (kab)
- This is used in the data calculation to merge Opinions into a Reputation.
-
-Local garbage collection, editing, enhancement and censorship
- A reputation server can sweep its objects and, based on local criteria:
- remove the object if:
- the signature/hash is no longer valid
- the signature cannot be validated (purely anonymous)
- the signature belongs to a low-reputation source
- (kab)this would normally be a system optimization on the server
-
+1. Sorting, ranking
+ a. results may be returned ranked according to local server rules
+ b. local reputation enhancement
+ i. the signature/content/object has high reputation
+ ii. the price(mojo)/KB, availability, speed, similar content types,
+ feature set (e.g. does it support query), etc. meets set levels
+
+2. Local editing, garbage collection, censorship, data store optimization
+ a. a reputation server can remove/edit objects based on local criteria:
+ i. the signature/hash is no longer valid
+ ii. the signature cannot be validated (purely anonymous)
+ iii. the signature belongs to a low-reputation source
+
+3. Reputation calculation (may require peer communications)
+ a. given an object, return its known reputation components
+ i. as a set of object grafts
+ ii. as a merged value (computed via a bias)
+ b. facility for 'blending' reputation results from multiple sources
+ i. may be used to merge 'Opinions' [into a 'Reputation' (kab)]
+
 Note the many possibilities for a local reputation server to affect results
     server reputation loss will occur when:
         if it is found to be too biased, unreliable, or random



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