[SOLVED] CSCI572 Homework 1

Web Search Engine Comparison

This exercise is about comparing the search results from Google versus different search engines. Many search engine comparison studies have been done. All of them use samples of data, some small and some large, so no definitive conclusions can be drawn. But it is always instructive to see how two search engines match up, even on a small data set.

The process you will follow is to issue a set of queries and to evaluate how closely the results of the two search engines compare. You will compare the results from the search engine that you are assigned to with the results from Google (provided by us on the class website).

To begin, the class is divided into four groups. Students are pre-assigned according to their USC ID number, as given in the table below.

Note: Please stick with the assigned dataset and search engine according to your ID number. PLEASE don’t work on another dataset and later ask for an exception.

USC ID ends with 01~25 26~50 51~75 76~99

THE QUERIES

Query Data Set Google Reference Assigned Search Dataset Engine

100QueriesSet1 Google_Result1.json Bing 100QueriesSet2 Google_Result2.json Yahoo! 100QueriesSet3 Google_Result3.json Ask 100QueriesSet4 Google_Result4.json Teoma

The queries will be given to you in a text file, one query per line. Each file contains 100 queries. These are actual queries extracted from query log files of several search engines. Here is a sample of some of the queries:

The European Union includes how many countries
What are Mia Hamms accomplishments
Which form of government is still in place in Greece When was the canal de panama built

What color is the black box on commercial airplanes

REFERENCE GOOGLE DATASET

A Google Reference JSON1 file is given which contains the Google results for each of the queries in your dataset. The JSON file is structured in the form of a query as the key and a list of 10 results as the value for that key (each a particular URL representing a result). The Google results for a specific query are ordered as they were returned by Google. Namely the 1st element in the list represents the top result that was scraped from Google, the 2nd element represents the second result, and so on. Example:

1 JSON, JavaScript object Notation is a file format used to transmit data objects consisting of key-value pairs. It is programming language independent. https://www.softwaretestinghelp.com/json-tutorial/

{
“A two dollar bill from 1953 is worth what”: [

       "http://www.antiquemoney.com/old-two-dollar-bill-value-price-guide/two-dollar-
bank-notes-pictures-prices-history/prices-for-two-dollar-1953-legal-tenders/",

“https://oldcurrencyvalues.com/1953_red_seal_two_dollar/”, “https://www.silverrecyclers.com/blog/1953-2-dollar-bill.aspx”, “https://www.ebay.com/b/1953-A-2-Dollar-Bill/40033/bn_7023293545”, “https://www.ebay.com/b/1953-2-US-Federal-Reserve-Small-

Notes/40029/bn_71222817”, “https://coinsite.com/why-the-1953-2-dollar-bill-has-a-red-seal/”, “https://hobbylark.com/collecting/Value-of-Two-Dollar-Bills”, “https://www.quora.com/What-is-the-value-of-a-2-dollar-bill-from-1953”, “https://www.reference.com/hobbies-games/1953-2-bill-worth-c778780b24b9eb8a”, “https://treasurepursuits.com/1953-2-dollar-bill-value-whats-it-worth/”
]

}

DETERMINING OVERLAP AND CORRELATION

Overlap: Since the Google results are taken as our baseline, it will be interesting to see how many identical results are returned by your assigned search engine, regardless of their position. Assuming Google’s results are the standard of relevance, the percentage of identical results will act as a measure of the quality of your assigned search engine.

Each of the queries in your dataset should be run on your assigned search engine. You should capture the top ten results. Only the resulting URL is required. For each of the top ten results for each query you should compute an overlap score between our reference Google dataset and your scraped results. The output format is described ahead.

Note: If you get less than 10 URLs for a particular query, you can just use those results to compare against Google results. For example: if a query gets 6 results from a search engine, just use those 6 results to compare against 10 results of Google reference dataset and produce statistics for that particular query.

• ●  di is the difference in the two rankings, and
• ●  n is the number of observations

Note:

Note: In the event that your search engine account enables personalized search, please turn this off before performing your tests.

Example1.1: “Who discovered x-rays in 1885”

GOOGLE RESULTS

1. https://explorable.com/wilhelm-conrad-roentgen
2. https://www.the-scientist.com/foundations/the-first-x-ray-1895-42279
3. https://www.bl.uk/learning/cult/bodies/xray/roentgen.html
4. https://en.wikipedia.org/wiki/Wilhelm_R%C3%B6ntgen
5. https://www.wired.com/2010/11/1108roentgen-stumbles-x-ray/
6. https://www.history.com/this-day-in-history/german-scientist-discovers-x-rays
7. https://www.aps.org/publications/apsnews/200111/history.cfm
8. https://www.nde-ed.org/EducationResources/CommunityCollege/Radiography/Introduction/history.htm 9. https://www.dw.com/en/x-ray-vision-an-accidental-discovery-that-revolutionized-medicine/a-18833060 10. http://www.slac.stanford.edu/pubs/beamline/25/2/25-2-assmus.pdf

RESULTS FROM ANOTHER SEARCH ENGINE 1. https://explorable.com/wilhelm-conrad-roentgen

2. https://www.history.com/this-day-in-history/german-scientist-discovers-x-rays
3. https://www.coursehero.com/file/p5jkhl/Discovery-of-X-rays-In-1885-Wilhem-Rontgen-while-studying-the-characteristics/ 4. http://www.nde-ed.org/EducationResources/HighSchool/Radiography/discoveryxrays.htm
5. https://www.answers.com/Q/Who_discovered_x-rays
6. https://www.aps.org/publications/apsnews/200111/history.cfm
7. https://www.answers.com/Q/Who_discovered_x-rays
8. https://www.coursehero.com/file/p5jkhl/Discovery-of-X-rays-In-1885-Wilhem-Rontgen-while-studying-the-characteristics/ 9. https://www.wired.com/2010/11/1108roentgen-stumbles-x-ray/
10. http://time.com/3649842/x-ray/

RANK MATCHES FROM GOOGLE AND ANOTHER SEARCH ENGINE

1 AND 1 5 AND 9 6 AND 2 7 AND 6 8 AND 4

We are now ready to compute Spearman’s rank correlation coefficient.

Rank Rank Google Other Srch

di di2

Engine 1100

5 9 -4 16 6 2 4 16 7611 8 4 4 16

The sum of di2 = 49. The value of n = 5. Substituting into the equation

1 – ( (6 * 49) / (5 * 24) ) = 1 – ( 294/120) = 1 – 2.45 = -1.45

Even though we have five overlapping results (50% overlap), their positions in the search result list produce a negative Spearman coefficient indicating that the overlapping results are uncorrelated. Clearly the two search engines are using different algorithms for weighting and ranking the documents they determine are most relevant to the query. Moreover their algorithms are emphasizing different ranking features.

Note: the value of n in the equation above refers to the number of URL matches (in this case, five) and does not refer to the original number of results (in this case, ten).

TASKS
Task1: Scraping results from your assigned search engine

In this task you need to develop a script (computer program) that could scrape the top 10 results from your assigned search engine. You may use any language of your choice. Always incorporate random delay between 10 to 100 seconds while scraping multiple queries, else you may be blocked off by the search engine and they may not allow you to scrape results for several hours. For reference:

• ●  https://pypi.org/project/beautifulsoup4, a python library for parsing HTML documents
• ●  URLs for the search engines:
  • ○  Bing: http://www.bing.com/search?q=
  • ○  Yahoo!: http://www.search.yahoo.com/search?p=
  • ○  Ask: http://www.ask.com/web?q=
  • ○  Teoma: https://www.teoma.com/web?q=

    For each URL, you can add your query string after q=

• ●  Selectors for various search engines, you grab links by looking for href in these selectors:
  • ○  Bing: [“li”, attrs = {“class” : “b_algo”}]
  • ○  Yahoo!: [“a”, attrs = {“class” : “ac-algo fz-l ac-21th lh-24”}]
  • ○  Ask: [“div”, attrs = {“class” : “PartialSearchResults-item-title”}]
  • ○  Teoma: [“a”, attrs = {“class” : “algo-title”}]

    By executing this task you need to generate a JSON file which will store your results in the JSON format described above and repeated here.

    {

    Query1: [Result1, Result2, Result3, Result4, Result5, Result6, Result7, Result8, Result9, Result10],

    Query2: [Result1, Result2, Result3, Result4, Result5, Result6, Result7, Result8, Result9, Result10],

    ….

           Query100: [Result1, Result2, Result3, Result4, Result5, Result6, Result7,
    Result8, Result9, Result10]
    }
    

    Here Result1 is the top result for that particular query.

    Task2: Determining the Percent Overlap and the Spearman Coefficient

    For this task, you need to use the JSON file that you generated in Task 1 and the Google reference dataset which is provided by us and compare the results as shown in the Determining Correlation section above. The output should be a CSV file with the following information:

1. Use the JSON file that you generated in Task 1 and do the following steps on each query:
2. Determine the URLs that match with the given reference Google dataset, and their

   position in the search engine result list

3. Compute the percent of overlap. In Example1.1, above the percent overlap is 5/10 or 50%.
4. Compute the Spearman correlation coefficient. In above Example1.1, the coefficient is -1.45.
5. Once you run all of the queries, collect all of the top ten URLs and compute the statistics, as shown in the following example:

Note: The above example is a table with four columns, rows containing results for each of the queries, and averages for each of the columns. Of course the actual values above are only for demonstration purposes.

Points to note:

• ●  Always incorporate a delay while scraping. We recommend that you use a random delay with a range of 10 to 100 seconds.
• ●  You will likely be blocked off from the search engine if you do not implement some delay in your code.
• ●  You should ignore the People Also Ask boxes and any carousels that may be included in the results.

  SUBMISSION INSTRUCTIONS

  Please place your homework in your Google Drive CSCI572 folder that is shared with your

grader, in the subfolder named hw1. You need to submit:

• ●  JSON file generated in Task 1 while scraping your assigned search engine.
• ●  CSV file of final results after determining relevance between your assigned search engine

  and Google reference dataset provided by us.

• ●  TXT file stating why the assigned search engine performed either better/worse/same as

  Google

  SAMPLE SCRAPING PROGRAM IN PYTHON

  Here is a program you can use to help you get started

     from bs4 import BeautifulSoup
     from time import sleep
     import requests
     from random import randint
  

from html.parser import HTMLParser

USER_AGENT = {'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64)
AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.100
Safari/537.36'}

class SearchEngine:
    @staticmethod

    def search(query, sleep=True):
        if sleep: # Prevents loading too many pages too soon

            time.sleep(randint(10, 100))
        temp_url = '+'.join(query.split()) #for adding + between words for

the query
        url = 'SEARCHING_URL' + temp_url

        soup = BeautifulSoup(requests.get(url, headers=USER_AGENT).text,
"html.parser")

        new_results = SearchEngine.scrape_search_result(soup)
        return new_results

    @staticmethod
    def scrape_search_result(soup):

        raw_results = soup.find_all("SEARCH SELECTOR")
        results = []
        #implement a check to get only 10 results and also check that URLs

must not be duplicated
        for result in raw_results:

            link = result.find('a').get('href')

            results.append(link)
        return results

#############Driver code############
SearchEngine.search("QUERY")
####################################

FAQs

1. What do I need to run Python on my Windows/Mac machine?
   You can refer to the documentation for setup: https://docs.python.org/3.6/using/index.html
   We encourage you to use Python 3.6. You can find many tutorials on Google.
2. Given that Python is installed what lines of the sample program do I have to modify to get it to work on a specific search engine?
   In the reference code, you need to:

   ● Supply in query variable
   ● Change SEARCHING_URL and SEARCH SELECTOR as per the search engine

   that is assigned to you
   ● Implement the code that extracts only top 10 URLs and make sure that none of

   them is repeated
   ● Implement the main function

3. What to do if the query does not produce ten results.
   You can modify the URLs to get 30 results on single page:
   • –  For bing use count=30 – http://www.bing.com/search?q=test&count=30
   • –  For yahoo use n=30 – https://search.yahoo.com/search?p=test&n=30

• –  For Ask and Teoma there does not appear to be a parameter which could produce n results on single page, so instead you can update the URL in such a manner which increments page number
• –  For Ask use page=2 – https://www.ask.com/web?q=testn&page=2
• –  For Teoma use page=2 – https://www.teoma.com/web?q=test&page=2

4. Two URLs that differ only in the scheme (http versus https) can be treated as the same.