# review word length, average weighted score, maximum word score, minimum
# word score, and pure mathematical average.
# From group result of the yelp_review_flat and selected category
# categories table: the categories user ever commented.
#
# Notice: guest database account will not have right to modify the database.
import psycopg2
import sys
import re
import scoresentence
TEST = False # True if generating test data. False for training data.
if __name__ == '__main__':
connection = scoresentence.dbConnect()
conn = connection[1]
cursor = connection[0]
cursor.execute("SELECT * FROM categories;")
cat = []
for item1 in cursor.fetchall():
cat.append(item1[1])
if (TEST):
end = "_test"
else:
end = ""
cursor.execute("SELECT distinct(uid) FROM features" + end + ";")
uid_set = cursor.fetchall()
count = 0
for uid in uid_set:
if OUTTOFILE:
print >> out, str(uid) + ", " + str(bid) + ", " + str(word_len) + ", " + str(weighted_score) + ", " + str(
maximum
) + ", " + str(minimum) + ", " + str(avg)
else:
print str(word_len) + ", " + str(weighted_score)
total = total + weighted_score
if weighted_score > maximum:
maximum = weighted_score
if weighted_score < minimum:
minimum = weighted_score
print "Average score is: " + str(total / len(score[4])) + "\nMaximum score is: " + str(
maximum
) + "\nMinimum score is: " + str(minimum)
if __name__ == "__main__":
connect = scoresentence.dbConnect()
cursor = connect[0]
conn = connect[1]
st = LancasterStemmer()
cursor.execute("SELECT avg(star_sum/number), avg((star_sum / number) * (star_sum / number)) from word_star;")
stat_data = cursor.fetchall()
avg_score = stat_data[0][0]
avg_score_square = stat_data[0][1]
std_dev = (float(avg_score_square) - (float(avg_score) ** (2))) ** (1 / 2.0)
score = scoreSentence(cursor, st, avg_score, std_dev)
printscore(score, OUTTOFILE, END)
cursor.close()
conn.close()
# This file is used to insert the generated file from getDataDistribution.py
# to the database.
#
# Notice: guest database account will not have right to modify the database.
import psycopg2
import sys
import re
import scoresentence
START = 1 # start file name
END = 2 # end file name
if __name__ == "__main__":
ret = scoresentence.dbConnect()
conn = ret[1]
cursor = ret[0]
for x in range(START, END):
count = 0
f = open("scoredistributiontop" + str(x) + "000.txt", 'r')
for line in f:
count = count + 1
split = line.strip().split(", ")
line = "INSERT INTO features_test values('" + split[
0] + "', '" + split[1] + "', " + split[2] + ", " + split[
3] + ", " + split[4] + ", " + split[5] + ", " + split[
6] + "); "
print "Insert into the row " + str(count)
cursor.execute(line)
conn.commit()
cursor.close()
# review word length, average weighted score, maximum word score, minimum
# word score, and pure mathematical average.
# From group result of the yelp_review_flat and selected category
# categories table: the categories user ever commented.
#
# Notice: guest database account will not have right to modify the database.
import psycopg2
import sys
import re
import scoresentence
TEST = False # True if generating test data. False for training data.
if __name__ == '__main__':
connection = scoresentence.dbConnect()
conn = connection[1]
cursor = connection[0]
cursor.execute("SELECT * FROM categories;")
cat = []
for item1 in cursor.fetchall():
cat.append(item1[1])
if (TEST):
end = "_test"
else:
end = ""
cursor.execute("SELECT distinct(uid) FROM features" + end + ";")
uid_set = cursor.fetchall()
count = 0
for uid in uid_set:
