web mining u3: slides done

This commit is contained in:
Michael Scholz 2013-06-02 14:05:54 +02:00
parent b0179a368b
commit 4722b4e7c4
7 changed files with 435 additions and 128 deletions

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@ -30,9 +30,12 @@
\section{1. Aufgabe}
\begin{frame}
\frametitle{1. Aufgabe \\ Daten besorgen, Klassen definieren}
.....
\begin{itemize}
\item benutzte Daten: vorgeschlagener couse/non-course Datensatz
\item Einteilung in Trainingsmenge/Testmenge: Erste Hälfte der alphabetisch sortieren Liste der Websites stellt die Testmenge dar.
\item course: 115 Elemente in Trainingsmenge / 115 Elemente in Testmenge
\item non-course: 410 Elemente in Trainingsmenge / 411 Elemente in Testmenge
\end{itemize}
\end{frame}
@ -43,9 +46,158 @@
\section{2. Aufgabe}
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
Transformation eines Textes (siehe /example/): \\
Am Beispiel:\\
course: http\_\^{}\^{}www.cs.utexas.edu\^{}users\^{}xfeng\^{}cs105\^{}cs105 \\
\vspace*{0.5cm}
\textbf{1. Schritt:} \\
\begin{itemize}
\item Extrahiere alle Wörter. Wort hat mind. 4 Zeichen und ist kein HTML-Element. Wörter werden lowercase behandelt und enthalten keine Zahlen.
\end{itemize}
\end{frame}
...
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
\textbf{Ergebnis Schritt 1:} \\
fall computer programming fall welcome homepage austin class taught will adams ajit george course announcement final over surprise contact xunnow make test most likely will solution homeworksreview sessions slidesthe slides second half semester please view them onlineif possible only print those really need printed files found updatedhomework source filemidterm solution webta information weekly timetableta section office hour location contact guana kumar natarajan tuesday thursday station utexas eduxun feng tuesday thursday station xfeng utexas detailed weekly time table this course course guide news group been this class news utexas class some notes class this homework also tips postscript file homework this friday here files homework homework file download files homework homework solution scored homework solution homework solution model solution homework will required some here wordlist linux provided warren wang wwang utexas notes midterm test notes review [...]
\end{frame}
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
\textbf{2. Schritt:} \\
\begin{itemize}
\item Filtere alle Stopwörter raus
\item Genutzt werden hier alle englsichen Stopwörter aus Übung 1
\end{itemize}
\end{frame}
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
\textbf{Ergebnis Schritt 2:} \\
fall computer programming fall welcome homepage austin class taught adams ajit george course announcement final surprise contact xunnow make test likely solution homeworksreview sessions slidesthe slides second half semester please view onlineif possible print really need printed files found updatedhomework source filemidterm solution webta information weekly timetableta section office hour location contact guana kumar natarajan tuesday thursday station utexas eduxun feng tuesday thursday station xfeng utexas detailed weekly time table course course guide news group class news utexas class notes class homework also tips postscript file homework friday files homework homework file download files homework homework solution scored homework solution homework solution model solution homework required wordlist linux provided warren wang wwang utexas notes midterm test notes review session answer exercises kumar notes review session model solution made modifications monday afternoon postscript file model solution ajit postscript file postscript file midterm solution homework files [...]
\end{frame}
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
\textbf{3. Schritt:} \\
\begin{itemize}
\item Stemming der Wörter
\item Genutzt wird eine Pythonimplementierung von PorterStemmer
\end{itemize}
\end{frame}
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
\textbf{Ergebnis Schritt 3:} \\
fall comput program fall welcom homepag austin class taught adam ajit georg cours announc final surpris contact xunnow make test like solut homeworksreview session slidesth slide second half semest pleas view onlineif possibl print realli need print file found updatedhomework sourc filemidterm solut webta inform weekli timetableta section offic hour locat contact guana kumar natarajan tuesdai thursdai station utexa eduxun feng tuesdai thursdai station xfeng utexa detail weekli time tabl cours cours guid new group class new utexa class note class homework also tip postscript file homework fridai file homework homework file download file homework homework solut score homework solut homework solut model solut homework requir wordlist linux provid warren wang wwang utexa note midterm test note review session answer exercis kumar note review session model solut made modif mondai afternoon postscript file model solut ajit postscript file postscript file midterm solut homework file decimalinteg decimalinteg hexinteg hexinteg octalinteg octalinteg slide section postscript [...]
\end{frame}
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
\textbf{4. Schritt:} \\
\begin{itemize}
\item Notiere Termfrequency für jeden Term des Dokuments
\item Sortiere Terme entsprechend der Termfrequency
\item tf(t, d) = f(t, d) $\to$ Termfrequenxy = Raw Frequency
\end{itemize}
\end{frame}
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
\textbf{Ergebnis Schritt 4:} \\
homework 16 solut 14 file 9 postscript 7 session 5 kumar 5 utexa 5 class 4 note 4 review 4 cours 3 slide 3 section 3 model 3 format 3 fall 2 comput 2 austin 2 ajit 2 contact 2 test 2 print 2 weekli 2 tuesdai 2 thursdai 2 station 2 feng 2 xfeng 2 new 2 midterm 2 decimalinteg 2 hexinteg 2 octalinteg 2 program 1 welcom 1 homepag 1 taught 1 adam 1 georg 1 announc 1 final 1 surpris 1 xunnow 1 make 1 like 1 homeworksreview 1 slidesth 1 second 1 half 1 semest 1 pleas 1 view 1 onlineif 1 possibl 1 realli 1 need 1 found 1 updatedhomework 1 sourc 1 filemidterm 1 webta 1 inform 1 timetableta 1 offic 1 hour 1 locat 1 guana 1 natarajan 1 eduxun 1 detail 1 time 1 tabl 1 guid 1 group 1 also 1 tip 1 fridai 1 download 1 score 1 requir 1 wordlist 1 linux 1 provid 1 warren 1 wang 1 wwang 1 answer 1 exercis 1 made 1 modif 1 mondai 1 afternoon 1 assign 1 maintain 1 edudepart 1 sciencesunivers 1 texa 1
\end{frame}
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
\textbf{5. Schritt:} \\
IDF für alle Dokumente der Testmenge berechnen: \\
\begin{equation*}
idf(t,D) = log(\frac{|D|}{|{d \in D : t \in d}|})
\end{equation*}
mit \\
|D| : Kardinalität von D \\
$|\{d \in D : t \in d\}|$ : Anzahl der Dokumente in denen ter Term auftritt
\end{frame}
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
\textbf{Ergebnis Schritt 5:} \\
{\small term, in dicuments count, idf, in c count, in nc count, wordid, relevance} \\
\begin{center}
{\tiny univers 283 0.617951 21 262 2 241\\
comput 385 0.310155 75 310 0 235 \\
scienc 328 0.470385 50 278 1 228 \\
home 354 0.394101 71 283 4 212 \\
page 368 0.355315 83 285 3 202 \\
research 215 0.892760 8 207 5 199\\
depart 232 0.816661 18 214 6 196\\
interest 212 0.906812 20 192 11 172\\
work 202 0.955131 28 174 13 146\\
washington 187 1.032290 22 165 124 143\\
madison 158 1.200803 9 149 823 140\\
wisconsin 161 1.181994 11 150 805 139\\
project 184 1.048463 27 157 20 130\\
engin 164 1.163532 18 146 19 128\\
system 210 0.916291 42 168 12 126 \\
wisc 240 0.782759 60 180 2574 120 \\
graduat 132 1.380596 7 125 24 118 \\
current 153 1.232960 19 134 16 115 \\
dayton 118 1.492714 3 115 8703 112 \\
student 168 1.139434 28 140 14 112 \\
seattl 110 1.562918 0 110 1034 110 \\
public 116 1.509808 13 103 27 90 \\
also 143 1.300554 29 114 31 85 \\
link 134 1.365558 25 109 44 84 \\
...}
\end{center}
\end{frame}
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
\textbf{6. Schritt:} \\
Berechne TF-IDF für jedes Dokument: \\
\begin{equation*}
tfidf(t,d,D) = tf(t,d) * idf(t,D)
\end{equation*}
\end{frame}
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
\textbf{Ergebnis Schritt 6:} \\
{\small term, tf, in documents count, idf, tfidf, wordid} \\
\begin{center}
{\tiny comput 2 390 0.299154 0.598308 0 \\
inform 1 209 0.922967 0.922967 17 \\
program 1 195 0.992302 0.992302 26 \\
utexa 5 182 1.061295 5.306475 9 \\
austin 2 157 1.209055 2.418110 8 \\
texa 1 150 1.254666 1.254666 10 \\
offic 1 147 1.274869 1.274869 98 \\
cours 3 144 1.295488 3.886464 165 \\
time 1 131 1.390104 1.390104 36 \\
also 1 116 1.511711 1.511711 31 \\
group 1 111 1.555771 1.555771 25 \\
contact 2 108 1.583170 3.166340 15 \\
class 4 103 1.630572 6.522288 230 \\
fall 2 90 1.765492 3.530984 184 \\
model 3 77 1.921496 5.764488 55 \\
note 4 75 1.947813 7.791252 247 \\
postscript 7 73 1.974842 13.823894 253 \\
file 9 71 2.002621 18.023589 944 \\
...}
\end{center}
\end{frame}
\begin{frame}
\frametitle{2. Aufgabe \\ Aufbereitung der Daten}
\textbf{7. Schritt:} \\
Daten in Sparse-Repräsentation überführen. \\
\textit{Beispiel (aus course):} \\
+1 11:1.117807 13:1.083518 17:0.922967 20:3.646335 29:1.196397 36:2.780208 42:3.203724 48:2.075646 51:2.060609 56:1.630572 58:8.067224 59:2.353278 64:3.842992 65:4.479900 66:32.945892 73:1.947813 93:2.738941 98:2.549738 104:15.926298 113:1.573953 \\
\vspace*{0.5cm}
\textit{Beispiel (aus non-course):} \\
-1 0:1.196616 5:0.890023 11:1.117807 13:1.083518 14:1.100515 17:0.922967 20:1.215445 21:1.680334 26:0.992302 29:1.196397 31:1.511711 36:1.390104 37:6.888024 39:20.168060 42:1.601862 48:2.075646 51:8.242436 55:3.842992 56:3.261144 57:4.244332 58:2.016806 59:4.706556 64:11.528976 66:16.472946 73:1.947813 77:1.583170 78:1.974842 90:4.746962 91:2.170957 98:2.549738 104:2.654383 109:2.415154 112:5.537588 113:3.147906
\end{frame}

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