[Gzz-commits] manuscripts/Paper paper.tex

[Tuomas J. Lukka]

CVSROOT:        /cvsroot/gzz
Module name:    manuscripts
Changes by:     Tuomas J. Lukka <address@hidden>        03/03/31 09:38:11

Modified files:
        Paper          : paper.tex 

Log message:
        Experiment rationale

CVSWeb URLs:
http://savannah.gnu.org/cgi-bin/viewcvs/gzz/manuscripts/Paper/paper.tex.diff?tr1=1.94&tr2=1.95&r1=text&r2=text

Patches:
Index: manuscripts/Paper/paper.tex
diff -u manuscripts/Paper/paper.tex:1.94 manuscripts/Paper/paper.tex:1.95
--- manuscripts/Paper/paper.tex:1.94    Mon Mar 31 09:28:24 2003
+++ manuscripts/Paper/paper.tex Mon Mar 31 09:38:10 2003
@@ -1306,7 +1306,7 @@
 }
 \end{figure}
 
-\subsection{Recognizability experiment}
+\subsection{An Initial Recognizability Experiment}
 
 %In our application visual texture discrimination is not as
 %much of an issue as memorizability and recognizability of
@@ -1326,22 +1326,26 @@
 
 In order to evaluate the recognizability of our procedurally generated
 textures, we need to have an appropriate comparison point.
-Pictures of natural objects would not provide a good comparsion,
+Pictures of natural objects would not be appropriate,
 because they cannot be generated in infinite amounts from seed
 numbers and they would esasily yield undesirable semantic associations.
-Thus, we simply use plain solid color backgrounds as a baseline for comparison
+Lacking a better example, we shall use plain solid color backgrounds 
+as a baseline 
 even though the colors of even a small set of randomly chosen colors would 
 most likely not be discriminable.
 
-Surely it would be hard to remember a large number of textures, too.
-However, the user does not have to remember all the textures;
-it suffices to learn the textures of the most often used documents
-and distinguish them from the rest:
+Another question is how many textures would the user have to remember
+for it to be useful.
+Studies of web cache statistics (see, e.g. \cite{breslau99web}) 
+have shown that file popularity approximately follows Zipf's law
+so that a small number of documents accounts 
+for most of the use,
+%Obviously, the user does not have to remember all the textures;
+%it suffices to learn the textures of the most often used documents
+%and distinguish them from the rest,
 see Fig.~\ref{fig-zipf}.
-Many studies of web cache statistics 
-have shown that for instance file popularity approximately follows Zipf's law
-(see, e.g. \cite{breslau99web}) so that a small number of documents accounts 
-for most of the use.
+
+
 %Also \cite{glassman94caching}, perhaps the first web cache zipf ref
 
 \begin{figure}
@@ -1359,7 +1363,7 @@
 Each square represents a document, and the area of each square is scaled
 to its rate of accesses.
 The diagram shows 2000 documents weighted with Zipf's law with exponent 1.1.
-Here, the 15 most important documents account for approximately half of the 
accesses.
+Under these conditions, the 15 most important documents account for 
approximately half of the accesses.
 Of course, it is impossible to know which documents will be important and 
 that will also change with time so all documents should be textured
 stably from the first viewing onwards.