使用 NLP 和 SQLite 的餐厅点评分析
原文:https://www . geesforgeks . org/restaurant-review-analysis-use-NLP-and-SQLite/
通常情况下，很多企业由于缺乏利润、缺乏适当的改进措施而被视为失败。大多数情况下，餐馆老板面临很多困难来提高他们的生产力。这个项目确实帮助了那些想提高生产力的人，这反过来又增加了他们的商业利润。这是这个项目的主要目标。
该项目所做的是，餐馆老板通过顾客的文本评论了解他的餐馆的缺点，例如他的餐馆最不喜欢的食物，该文本评论用最大似然分类算法(朴素贝叶斯)处理，其结果用 SQLite 存储在数据库中。
使用的工具和技术:
- 我是 NLTK
- 机器学习
- 计算机编程语言
- Tkinter
- Sqlite3
- 熊猫
逐步实施:
步骤 1:导入库和初始化数据
首先，我们导入 NumPy 、 matplotlib 、 pandas 、nltk、re、sklearn、 Tkinter 、sqlite3 库，这些库用于数据操作、文本数据处理、模式识别、数据训练、图形用户界面和数据库上的数据操作。
Python 3
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import re
import nltk
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.model_selection import train_test_split
from sklearn.naive_bayes import GaussianNB
from sklearn.metrics import accuracy_score
from tkinter import *
import sqlite3
dataset = pd.read_csv('Restaurant_Reviews.tsv',
delimiter='\t', quoting=3)
corpus = []
rras_code = "Wyd^H3R"
food_rev = {}
food_perc = {}
conn = sqlite3.connect('Restaurant_food_data.db')
c = conn.cursor()
for i in range(0, 1000):
review = re.sub('[^a-zA-Z]', ' ', dataset['Review'][i])
review = review.lower()
review = review.split()
ps = PorterStemmer()
all_stopwords = stopwords.words('english')
all_stopwords.remove('not')
review = [ps.stem(word)
for word in review if not word in set(all_stopwords)]
review = ' '.join(review)
corpus.append(review)
cv = CountVectorizer(max_features=1500)
X = cv.fit_transform(corpus).toarray()
y = dataset.iloc[:, -1].values
X_train, X_test, y_train, y_test = train_test_split(
X, y, test_size=0.20, random_state=0)
classifier = GaussianNB()
classifier.fit(X_train, y_train)
y_pred = classifier.predict(X_test)
variables = []
clr_variables = []
foods = ["Idly", "Dosa", "Vada", "Roti", "Meals", "Veg Biryani",
"Egg Biryani", "Chicken Biryani", "Mutton Biryani",
"Ice Cream", "Noodles", "Manchooriya", "Orange juice",
"Apple Juice", "Pineapple juice", "Banana juice"]
for i in foods:
food_rev[i] = []
food_perc[i] = [0.0, 0.0]
def init_data():
conn = sqlite3.connect('Restaurant_food_data.db')
c = conn.cursor()
for i in range(len(foods)):
c.execute("INSERT INTO item VALUES(:item_name,:no_of_customers,\
:no_of_positives,:no_of_negatives,:pos_perc,:neg_perc)",
{
'item_name': foods[i],
'no_of_customers': "0",
'no_of_positives': "0",
'no_of_negatives': "0",
'pos_perc': "0.0%",
'neg_perc': "0.0%"
}
)
conn.commit()
conn.close()
第二步:向用户说明
最初，我们的图形用户界面应用程序询问用户他是所有者还是客户，以决定要执行什么操作。
Python 3
root1 = Tk()
main = "Restaurant Review Analysis System/"
root1.title(main+"Welcome Page")
label = Label(root1, text="RESTAURANT REVIEW ANALYSIS SYSTEM",
bd=2, font=('Arial', 47, 'bold', 'underline'))
ques = Label(root1, text="Are you a Customer or Owner ???")
cust = Button(root1, text="Customer", font=('Arial', 20),
padx=80, pady=20, command=take_review)
owner = Button(root1, text="Owner", font=('Arial', 20),
padx=100, pady=20, command=login)
'''conn=sqlite3.connect('Restaurant_food_data.db')
c=conn.cursor()
c.execute("CREATE TABLE item (Item_name text,No_of_customers text,\
No_of_positive_reviews text,No_of_negative_reviews text,Positive_percentage \
text,Negative_percentage text) ")
conn.commit()
conn.close()'''
#c.execute("DELETE FROM item")
root1.attributes("-zoomed", True)
label.grid(row=0, column=0)
ques.grid(row=1, column=0, sticky=W+E)
ques.config(font=("Helvetica", 30))
cust.grid(row=2, column=0)
owner.grid(row=3, column=0)
conn.commit()
conn.close()
root1.mainloop()
澄清用户
第三步:收集数据
一旦系统确定用户是顾客，它就会要求以文本格式进行食品审查。顾客必须选择他从餐馆拿走的食物，然后对选择的食物进行评论。当他点击提交按钮时，文本评论将在最大似然算法下处理，以预测它是正面评论还是负面评论。然后，整个数据被插入数据库。
Python 3
def take_review():
root2 = Toplevel()
root2.title(main+"give review")
label = Label(root2, text="RESTAURANT REVIEW ANALYSIS SYSTEM",
bd=2, font=('Arial', 47, 'bold', 'underline'))
req1 = Label(root2, text="Select the item(s) you have taken.....")
conn = sqlite3.connect('Restaurant_food_data.db')
c = conn.cursor()
chk_btns = []
selected_foods = []
req2 = Label(root2, text="Give your review below....")
rev_tf = Entry(root2, width=125, borderwidth=5)
req3 = Label(root2, text="NOTE : Use not instead of n't.")
global variables
variables = []
chk_btns = []
for i in range(len(foods)):
var = IntVar()
chk = Checkbutton(root2, text=foods[i], variable=var)
variables.append(var)
chk_btns.append(chk)
label.grid(row=0, column=0, columnspan=4)
req1.grid(row=1, column=0, columnspan=4, sticky=W+E)
req1.config(font=("Helvetica", 30))
for i in range(4):
for j in range(4):
c = chk_btns[i*4+j]
c.grid(row=i+3, column=j, columnspan=1, sticky=W)
selected_foods = []
submit_review = Button(root2, text="Submit Review", font=(
'Arial', 20), padx=100, pady=20, command=lambda: [
estimate(rev_tf.get()), root2.destroy()])
root2.attributes("-zoomed", True)
req2.grid(row=7, column=0, columnspan=4, sticky=W+E)
req2.config(font=("Helvetica", 20))
rev_tf.grid(row=8, column=1, rowspan=3, columnspan=2, sticky=S)
req3.grid(row=11, column=1, columnspan=2)
submit_review.grid(row=12, column=0, columnspan=4)
conn.commit()
conn.close()
# Processing and storing the data
def estimate(s):
conn = sqlite3.connect('Restaurant_food_data.db')
c = conn.cursor()
review = re.sub('[^a-zA-Z]', ' ', s)
review = review.lower()
review = review.split()
ps = PorterStemmer()
all_stopwords = stopwords.words('english')
all_stopwords.remove('not')
review = [ps.stem(word)
for word in review if not word in set(all_stopwords)]
review = ' '.join(review)
X = cv.transform([review]).toarray()
res = classifier.predict(X) # list
if "not" in review:
res[0] = abs(res[0]-1)
selected_foods = []
for i in range(len(foods)):
if variables[i].get() == 1:
selected_foods.append(foods[i])
c.execute("SELECT *,oid FROM item")
records = c.fetchall()
for i in records:
rec = list(i)
if rec[0] in selected_foods:
n_cust = int(rec[1])+1
n_pos = int(rec[2])
n_neg = int(rec[3])
if res[0] == 1:
n_pos += 1
else:
n_neg += 1
pos_percent = round((n_pos/n_cust)*100, 1)
neg_percent = round((n_neg/n_cust)*100, 1)
c.execute("""UPDATE item SET Item_name=:item_name,No_of_customers\
=:no_of_customers,No_of_positive_reviews=:no_of_positives,\
No_of_negative_reviews=:no_of_negatives,Positive_percentage\
=:pos_perc,Negative_percentage=:neg_perc where oid=:Oid""",
{
'item_name': rec[0],
'no_of_customers': str(n_cust),
'no_of_positives': str(n_pos),
'no_of_negatives': str(n_neg),
'pos_perc': str(pos_percent)+"%",
'neg_perc': str(neg_percent)+"%",
'Oid': foods.index(rec[0])+1
}
)
selected_foods = []
conn.commit()
conn.close()
复习
步骤 4:验证所有权
如果系统的当前用户是餐馆的所有者，则系统通过询问 rras_code(即唯一标识全世界餐馆的代码)来验证所有者。并且它是高度机密的，除了餐馆的共同所有者之外，人们不应该与其他人共享这个代码)。
Python 3
def login():
root3 = Toplevel()
root3.title(main+"owner verification")
label = Label(root3, text="RESTAURANT REVIEW ANALYSIS SYSTEM",
bd=2, font=('Arial', 47, 'bold', 'underline'))
label2 = Label(root3, text="VERIFY OWNERSHIP", bd=1,
font=('Helvetica', 30, 'bold', 'underline'))
label3 = Label(root3, text="To verify your ownership, please \
enter your restaurant's private rras code....",
bd=1, font=('Helvetica', 20, 'bold'))
ent = Entry(root3, show="*", borderwidth=2)
submit_code = Button(root3, text="Submit", font=('Arial', 20), padx=80,
pady=20, command=lambda: [
view_details(ent.get()), root3.destroy()])
root3.attributes("-zoomed", True)
label.grid(row=0, column=0, columnspan=3)
label2.grid(row=1, column=0, sticky=W+E, columnspan=3)
label3.grid(row=2, column=0, sticky=W, columnspan=3)
ent.grid(row=3, column=1, columnspan=1)
submit_code.grid(row=4, column=1, columnspan=1)
验证所有权
步骤 5:访问数据
当所有权得到验证时，所有者在新页面上有 3 个选项，如下所述:
Python 3
def popup():
messagebox.showerror("Error Message!", "Incorrect code!")
def view_details(s):
if(s != rras_code):
popup()
else:
root4 = Toplevel()
root4.title(main+"view_details")
label = Label(root4, text="RESTAURANT REVIEW ANALYSIS SYSTEM",
bd=2, font=('Arial', 47, 'bold', 'underline'))
sug1 = Label(
root4, text="Click the below button, if you want to view\
the data from your database....")
acc_btn = Button(root4, text="View Data", font=(
'Arial', 20), padx=100, pady=20, command=access_data)
sug2 = Label(root4, text="Click the below button, if you want \
to clear specific item data...")
itemclr_btn = Button(root4, text="Clear Item Data", font=(
'Arial', 20), padx=100, pady=20, command=clr_itemdata)
sug3 = Label(root4, text="Click the below button, if you want to\
clear all item data...")
allclr_btn = Button(root4, text="Clear All Data", font=(
'Arial', 20), padx=100, pady=20, command=clr_alldata)
exit_btn = Button(root4, text="Exit", command=root4.destroy)
root4.attributes("-zoomed", True)
label.grid(row=0, column=0)
sug1.grid(row=1, column=0)
sug1.config(font=("Helvetica", 30))
acc_btn.grid(row=2, column=0)
sug2.grid(row=3, column=0)
sug2.config(font=("Helvetica", 30))
itemclr_btn.grid(row=4, column=0)
sug3.grid(row=5, column=0)
sug3.config(font=("Helvetica", 30))
allclr_btn.grid(row=6, column=0)
exit_btn.grid(row=9, column=0, sticky=S)
选择
步骤 6:查看数据
所有者可以查看数据库中的数据，其中每种食物都具有诸如顾客数量、正面评价数量、负面评价数量、正面率、负面率等属性。高阳性食品用绿色标注，最低阳性食品用红色标注，以便于理解数据摘要。现在，主人可以识别低等级的食物，并试图通过采取一些措施来改善食物的味道，比如叫新厨师等。，这无疑改善了他的业务。
Python 3
def access_data():
root5 = Toplevel()
root5.title(main+"Restaurant_Database")
label = Label(root5, text="RESTAURANT REVIEW ANALYSIS SYSTEM",
bd=2, font=('Arial', 47, 'bold', 'underline'))
title1 = Label(root5, text="S.NO", font=('Arial', 10, 'bold', 'underline'))
title2 = Label(root5, text="FOOD ITEM", font=(
'Arial', 10, 'bold', 'underline'))
title3 = Label(root5, text="NO.OF CUSTOMERS",
font=('Arial', 10, 'bold', 'underline'))
title4 = Label(root5, text="NO.OF POSITIVE REVIEWS",
font=('Arial', 10, 'bold', 'underline'))
title5 = Label(root5, text="NO.OF NEGATIVE REVIEWS",
font=('Arial', 10, 'bold', 'underline'))
title6 = Label(root5, text="POSITIVE RATE",
font=('Arial', 10, 'bold', 'underline'))
title7 = Label(root5, text="NEGATIVE RATE",
font=('Arial', 10, 'bold', 'underline'))
label.grid(row=0, column=0, columnspan=7)
title1.grid(row=1, column=0)
title2.grid(row=1, column=1)
title3.grid(row=1, column=2)
title4.grid(row=1, column=3)
title5.grid(row=1, column=4)
title6.grid(row=1, column=5)
title7.grid(row=1, column=6)
conn = sqlite3.connect('Restaurant_food_data.db')
c = conn.cursor()
c.execute("SELECT *,oid from item")
records = c.fetchall()
pos_rates = []
for record in records:
record = list(record)
pos_rates.append(float(record[-3][:-1]))
max_pos = max(pos_rates)
min_pos = min(pos_rates)
for i in range(len(records)):
rec_list = list(records[i])
if str(max_pos)+"%" == rec_list[-3]:
rec_lab = [Label(root5, text=str(rec_list[-1]), fg="green")]
for item in rec_list[:-1]:
lab = Label(root5, text=item, fg="green")
rec_lab.append(lab)
elif str(min_pos)+"%" == rec_list[-3]:
rec_lab = [Label(root5, text=str(rec_list[-1]), fg="red")]
for item in rec_list[:-1]:
lab = Label(root5, text=item, fg="red")
rec_lab.append(lab)
else:
rec_lab = [Label(root5, text=str(rec_list[-1]))]
for item in rec_list[:-1]:
lab = Label(root5, text=item)
rec_lab.append(lab)
for j in range(len(rec_lab)):
rec_lab[j].grid(row=i+2, column=j)
exit_btn = Button(root5, text="Exit", command=root5.destroy)
exit_btn.grid(row=len(records)+5, column=3)
conn.commit()
conn.close()
root5.attributes("-zoomed", True)
数据库内容
步骤 7:清除数据:
当进行了一些调整或修改时，所有者可以清除那些特定的项目数据，以便他可以快速观察食品的性能。如果主人愿意，他也可以清除所有食品项目数据。
Python 3
def clr_itemdata():
root6 = Toplevel()
root6.title(main+"clear_item_data")
label = Label(root6, text="RESTAURANT REVIEW ANALYSIS SYSTEM",
bd=2, font=('Arial', 47, 'bold', 'underline'))
req1 = Label(root6, text="Pick the items to clear their corresponding\
item data....")
chk_list = []
global clr_variables
clr_variables = []
for i in range(len(foods)):
var = IntVar()
chk = Checkbutton(root6, text=foods[i], variable=var)
clr_variables.append(var)
chk_list.append(chk)
label.grid(row=0, column=0, columnspan=4)
req1.grid(row=1, column=0, columnspan=4, sticky=W+E)
req1.config(font=("Helvetica", 30))
for i in range(4):
for j in range(4):
c = chk_list[i*4+j]
c.grid(row=i+3, column=j, columnspan=1, sticky=W)
clr_item = Button(root6, text="Clear", font=(
'Arial', 20), padx=100, pady=20, command=lambda: [
clr_data(), root6.destroy()])
clr_item.grid(row=8, column=0, columnspan=4)
root6.attributes("-zoomed", True)
def clr_alldata():
confirm = messagebox.askquestion(
"Confirmation", "Are you sure to delete all data??")
if confirm == "yes":
conn = sqlite3.connect('Restaurant_food_data.db')
c = conn.cursor()
for i in range(len(foods)):
c.execute("""UPDATE item SET Item_name=:item_name,No_of_customers\
=:no_of_customers,No_of_positive_reviews=:no_of_positives,\
No_of_negative_reviews=:no_of_negatives,Positive_percentage=:\
pos_perc,Negative_percentage=:neg_perc where oid=:Oid""",
{
'item_name': foods[i],
'no_of_customers': "0",
'no_of_positives': "0",
'no_of_negatives': "0",
'pos_perc': "0.0%",
'neg_perc': "0.0%",
'Oid': i+1
}
)
conn.commit()
conn.close()
清除食品项目数据
最后，这是我用技术提高企业生产力的想法。这样，业务问题就会因生产率的提高而停止。
现实生活中的项目应用:
- 它可以在任何餐厅/酒店使用。
- 有效的食品改善措施，直接改善一个人的业务。
- 用户友好的。
- 没有业务损失的可能。
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