1 files changed, 0 insertions, 151 deletions
diff --git a/src/Chapter5/text/ExtractTopKeywords.java b/src/Chapter5/text/ExtractTopKeywords.java
deleted file mode 100644
index 8ab412a..0000000
--- a/src/Chapter5/text/ExtractTopKeywords.java
+++ /dev/null
@@ -1,151 +0,0 @@
-/* TweetTracker. Copyright (c) Arizona Board of Regents on behalf of Arizona State University
- * @author shamanth
- */
-package Chapter5.text;
-
-import java.io.BufferedReader;
-import java.io.File;
-import java.io.FileInputStream;
-import java.io.IOException;
-import java.io.InputStreamReader;
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.HashMap;
-import java.util.Set;
-import java.util.logging.Level;
-import java.util.logging.Logger;
-import org.json.JSONArray;
-import org.json.JSONException;
-import org.json.JSONObject;
-import utils.Tags;
-import utils.TextUtils;
-
-public class ExtractTopKeywords
-{
-
-    static final String DEF_INFILENAME = "ows.json";
-    static final int DEF_K = 60;
-    
-    /**
-     * Extracts the most frequently occurring keywords from the tweets by processing them sequentially. Stopwords are ignored.
-     * @param inFilename File containing a list of tweets as JSON objects
-     * @param K Count of the top keywords to return
-     * @param ignoreHashtags If true, hashtags are not considered while counting the most frequent keywords
-     * @param ignoreUsernames If true, usernames are not considered while counting the most frequent keywords
-     * @param tu TextUtils object which handles the stopwords
-     * @return a JSONArray containing an array of JSONObjects. Each object contains two elements "text" and "size" referring to the word and it's frequency
-     */
-    public JSONArray GetTopKeywords(String inFilename, int K, boolean ignoreHashtags, boolean ignoreUsernames, TextUtils tu)
-    {
-        HashMap<String, Integer> words = new HashMap<String,Integer>();
-        BufferedReader br = null;
-        try{
-            br = new BufferedReader(new InputStreamReader(new FileInputStream(inFilename),"UTF-8"));            
-            String temp = "";
-            while((temp = br.readLine())!=null)
-            {
-                try{
-                    JSONObject tweetobj = new JSONObject(temp);
-                    if(!tweetobj.isNull("text"))
-                    {
-                        String text = tweetobj.getString("text");
-                        //System.out.println(text);
-                        text = text.toLowerCase().replaceAll("\\s+", " ");
-                        /** Step 1: Tokenize tweets into individual words. and count their frequency in the corpus
-                           * Remove stop words and special characters. Ignore user names and hashtags if the user chooses to.
-                           */
-                        HashMap<String,Integer> tokens = tu.TokenizeText(text,ignoreHashtags,ignoreUsernames);
-                        Set<String> keys = tokens.keySet();
-                        for(String key:keys)
-                        {
-                            if(words.containsKey(key))
-                            {
-                                words.put(key, words.get(key)+tokens.get(key));
-                            }
-                            else
-                            {
-                                words.put(key, tokens.get(key));
-                            }
-                        }
-                    }
-                }catch(JSONException ex)
-                {
-                    ex.printStackTrace();
-                }
-            }
-        }catch(IOException ex)
-        {
-            ex.printStackTrace();
-        }finally{
-            try {
-                br.close();
-            } catch (IOException ex) {
-                Logger.getLogger(ExtractTopKeywords.class.getName()).log(Level.SEVERE, null, ex);
-            }
-        }        
-        Set<String> keys = words.keySet();
-        ArrayList<Tags> tags = new ArrayList<Tags>();
-        for(String key:keys)
-        {
-            Tags tag = new Tags();
-            tag.setKey(key);
-            tag.setValue(words.get(key));
-            tags.add(tag);
-        }
-        // Step 2: Sort the words in descending order of frequency
-        Collections.sort(tags, Collections.reverseOrder());
-        JSONArray cloudwords = new JSONArray();
-        int numwords = K;
-        if(tags.size()<numwords)
-        {
-            numwords = tags.size();
-        }        
-        for(int i=0;i<numwords;i++)
-        {
-            JSONObject wordfreq = new JSONObject();
-            Tags tag = tags.get(i);
-            try{
-                wordfreq.put("text", tag.getKey());
-                wordfreq.put("size",tag.getValue());
-                cloudwords.put(wordfreq);
-            }catch(JSONException ex)
-            {
-                ex.printStackTrace();
-            }
-        }
-        return cloudwords;
-    }
-
-    public static void main(String[] args)
-    {
-        ExtractTopKeywords etk = new ExtractTopKeywords();
-
-        //Initialize the TextUtils class which handles all the processing of text.
-        TextUtils tu = new TextUtils();
-        tu.LoadStopWords("C:/tweettracker/stopwords.txt");        
-        String infilename = DEF_INFILENAME;
-        int K = DEF_K;
-        if(args!=null)
-        {
-            if(args.length>=1&&!args[0].isEmpty())
-            {
-                File fl = new File(args[0]);
-                if(fl.exists())
-                {
-                    infilename = args[0];
-                }
-            }
-            if(args.length>=2&&!args[1].isEmpty())
-            {
-                try{
-                    K = Integer.parseInt(args[1]);
-                }catch(NumberFormatException ex)
-                {
-                    ex.printStackTrace();
-                }
-            }
-        }
-        System.out.println(etk.GetTopKeywords(infilename, K, false,true,tu));
-    }
-
-}