In this project, you will create a simple search engine for the website https://www.lawfareblog.com. This website provides legal analysis on US national security issues. You will use pagerank to return only the most important results from this website in your search engine.
Due date: Sunday, 22 29 September at midnight
Late Policy: You lose
Collaboration Policy: Do whatever will help you learn, but be an adult. You may talk to other students and use Google/ChatGPT. Recall that you will have an in-person oral exam on this material and the exam is worth many more points. The main purpose of this project is to help prepare you for the exam.
Data:
The data folder contains two files that store example "web graphs".
The file small.csv.gz contains the example graph from the Deeper Inside Pagerank paper.
This is a small graph, so we can manually inspect the contents of this file with the following command:
$ zcat data/small.csv.gz
source,target
1,2
1,3
3,1
3,2
3,5
4,5
4,6
5,6
5,4
6,4
Recall: The
catterminal command outputs the contents of a file to stdout, and thezcatcommand first decompressed a gzipped file and then outputs the decompressed contents.In python, we can use the built-in
gzipmodule to access gzipped files. The following python code is equivalent to the bash code above:>>> import gzip >>> fin = gzip.open('data/small.csv.gz', mode='rt') >>> print(fin.read()) source,target 1,2 1,3 3,1 3,2 3,5 4,5 4,6 5,6 5,4 6,4There are many terminal commands throughout these instructions. If you haven't used the terminal before, and so these commands are unfamiliar, that's okay. I'd be happy to explain them in office hours, or there are many tutors in the QCL available who can help. (There are no tutors for this class specifically, but anyone who has taken CSCI046 or CSCI133 with me will be able to help with the terminal.)
Furthermore, you don't "need" to understand the terminal commands in detail, since you are not required to run these commands or to create your own. The important part is to understand the English language description of what the commands are doing, and to understand that this is just how I computed what the English language text is describing.
As you can see, the graph is stored as a CSV file. The first line is a header, and each subsequent line stores a single edge in the graph. The first column contains the source node of the edge and the second column the target node. The file is assumed to be sorted alphabetically.
The second data file lawfareblog.csv.gz contains the link structure for the lawfare blog.
Let's take a look at the first 10 of these lines:
$ zcat data/lawfareblog.csv.gz | head
source,target
www.lawfareblog.com/,www.lawfareblog.com/topic/interrogation
www.lawfareblog.com/,www.lawfareblog.com/upcoming-events
www.lawfareblog.com/,www.lawfareblog.com/
www.lawfareblog.com/,www.lawfareblog.com/our-comments-policy
www.lawfareblog.com/,www.lawfareblog.com/litigation-documents-related-appointment-matthew-whitaker-acting-attorney-general
www.lawfareblog.com/,www.lawfareblog.com/topic/lawfare-research-paper-series
www.lawfareblog.com/,www.lawfareblog.com/topic/book-reviews
www.lawfareblog.com/,www.lawfareblog.com/documents-related-mueller-investigation
www.lawfareblog.com/,www.lawfareblog.com/topic/international-law-loac
You can see that in this file, the node names are URLs.
Semantically, each line corresponds to an HTML <a> tag that is contained in the source webpage and links to the target webpage.
We can use the following command to count the total number of links in the file:
$ zcat data/lawfareblog.csv.gz | wc -l
1610789
Since every link corresponds to a non-zero entry in the wc -l command also counts the header line, not just the data lines.)
To get the dimensions of
$ zcat data/lawfareblog.csv.gz | cut -f1 -d, | uniq | wc -l
25761
This matrix is large enough that computing matrix products for dense matrices takes several minutes on a single CPU. Fortunately, however, the matrix is very sparse. The following python code computes the fraction of entries in the matrix with non-zero values:
>>> 1610788 / (25760**2)
0.0024274297384360172
Thus, by using sparse matrix operations, we will be able to speed up the code significantly.
Code:
The pagerank.py file contains code for loading the graph CSV files and searching through their nodes for key phrases.
For example, you can perform a search for all nodes (i.e. urls) that mention the string corona with the following command:
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose --search_query=corona
NOTE: It will take about 10 seconds to load and parse the data files. All the other computation happens essentially instantly.
Currently, the pagerank of the nodes is not currently being calculated correctly, and so the webpages are returned in an arbitrary order. Your task in this assignment will be to fix these calculations in order to have the most important results (i.e. highest pagerank results) returned first.
Implement the WebGraph.power_method function in pagerank.py for computing the pagerank vector by fixing the FIXME: Task 1 annotation.
NOTE: The power method is the only data mining algorithm you will implement in class. You are implementing it because there are no standard library implementations available. Why?
- The runtime is heavily dependent on the data structures used to store the graph data. Different applications will need to use different data structures.
- It is "trivial" to implement. My solution to this homework is <10 lines of code.
Part 1:
To check that your implementation is working,
you should run the program on the data/small.csv.gz graph.
For my implementation, I get the following output.
$ python3 pagerank.py --data=data/small.csv.gz --verbose
DEBUG:root:computing indices
DEBUG:root:computing values
DEBUG:root:i=0 residual=2.5629e-01
DEBUG:root:i=1 residual=1.1841e-01
DEBUG:root:i=2 residual=7.0701e-02
DEBUG:root:i=3 residual=3.1815e-02
DEBUG:root:i=4 residual=2.0497e-02
DEBUG:root:i=5 residual=1.0108e-02
DEBUG:root:i=6 residual=6.3716e-03
DEBUG:root:i=7 residual=3.4228e-03
DEBUG:root:i=8 residual=2.0879e-03
DEBUG:root:i=9 residual=1.1750e-03
DEBUG:root:i=10 residual=7.0131e-04
DEBUG:root:i=11 residual=4.0321e-04
DEBUG:root:i=12 residual=2.3800e-04
DEBUG:root:i=13 residual=1.3812e-04
DEBUG:root:i=14 residual=8.1083e-05
DEBUG:root:i=15 residual=4.7251e-05
DEBUG:root:i=16 residual=2.7704e-05
DEBUG:root:i=17 residual=1.6164e-05
DEBUG:root:i=18 residual=9.4778e-06
DEBUG:root:i=19 residual=5.5066e-06
DEBUG:root:i=20 residual=3.2042e-06
DEBUG:root:i=21 residual=1.8612e-06
DEBUG:root:i=22 residual=1.1283e-06
DEBUG:root:i=23 residual=6.1907e-07
INFO:root:rank=0 pagerank=6.6270e-01 url=4
INFO:root:rank=1 pagerank=5.2179e-01 url=6
INFO:root:rank=2 pagerank=4.1434e-01 url=5
INFO:root:rank=3 pagerank=2.3175e-01 url=2
INFO:root:rank=4 pagerank=1.8590e-01 url=3
INFO:root:rank=5 pagerank=1.6917e-01 url=1
Yours likely won't be identical (due to minor implementation details and weird floating point issues), but it should be similar. In particular, the ranking of the nodes/urls should be the same order.
NOTE: The
--verboseflag causes all of the lines beginning withDEBUGto be printed. By default, only lines beginning withINFOare printed.
NOTE: There are no automated test cases to pass for this assignment. Test cases for algorithms involving floating point computations are hard to write and understand. Minor-seeming implementations details can have large impacts on the final result. These software engineering issues are beyond the scope of this class.
Instructions for how I will grade your homework are contained in the submission section at the end of this document.
Part 2:
The pagerank.py file has an option --search_query, which takes a string as a parameter.
If this argument is used, then the program returns all nodes that match the query string sorted according to their pagerank.
Essentially, this gives us the most important pages related to our query.
Again, you may not get the exact same results as me, but you should get similar results to the examples I've shown below. Verify that you do in fact get similar results.
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --search_query='corona'
INFO:root:rank=0 pagerank=1.0038e-03 url=www.lawfareblog.com/lawfare-podcast-united-nations-and-coronavirus-crisis
INFO:root:rank=1 pagerank=8.9224e-04 url=www.lawfareblog.com/house-oversight-committee-holds-day-two-hearing-government-coronavirus-response
INFO:root:rank=2 pagerank=7.0390e-04 url=www.lawfareblog.com/britains-coronavirus-response
INFO:root:rank=3 pagerank=6.9153e-04 url=www.lawfareblog.com/prosecuting-purposeful-coronavirus-exposure-terrorism
INFO:root:rank=4 pagerank=6.7041e-04 url=www.lawfareblog.com/israeli-emergency-regulations-location-tracking-coronavirus-carriers
INFO:root:rank=5 pagerank=6.6256e-04 url=www.lawfareblog.com/why-congress-conducting-business-usual-face-coronavirus
INFO:root:rank=6 pagerank=6.5046e-04 url=www.lawfareblog.com/congressional-homeland-security-committees-seek-ways-support-state-federal-responses-coronavirus
INFO:root:rank=7 pagerank=6.3620e-04 url=www.lawfareblog.com/paper-hearing-experts-debate-digital-contact-tracing-and-coronavirus-privacy-concerns
INFO:root:rank=8 pagerank=6.1248e-04 url=www.lawfareblog.com/house-subcommittee-voices-concerns-over-us-management-coronavirus
INFO:root:rank=9 pagerank=6.0187e-04 url=www.lawfareblog.com/livestream-house-oversight-committee-holds-hearing-government-coronavirus-response
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --search_query='trump'
INFO:root:rank=0 pagerank=5.7826e-03 url=www.lawfareblog.com/trump-asks-supreme-court-stay-congressional-subpeona-tax-returns
INFO:root:rank=1 pagerank=5.2338e-03 url=www.lawfareblog.com/document-trump-revokes-obama-executive-order-counterterrorism-strike-casualty-reporting
INFO:root:rank=2 pagerank=5.1297e-03 url=www.lawfareblog.com/trump-administrations-worrying-new-policy-israeli-settlements
INFO:root:rank=3 pagerank=4.6599e-03 url=www.lawfareblog.com/dc-circuit-overrules-district-courts-due-process-ruling-qasim-v-trump
INFO:root:rank=4 pagerank=4.5934e-03 url=www.lawfareblog.com/donald-trump-and-politically-weaponized-executive-branch
INFO:root:rank=5 pagerank=4.3071e-03 url=www.lawfareblog.com/how-trumps-approach-middle-east-ignores-past-future-and-human-condition
INFO:root:rank=6 pagerank=4.0935e-03 url=www.lawfareblog.com/why-trump-cant-buy-greenland
INFO:root:rank=7 pagerank=3.7591e-03 url=www.lawfareblog.com/oral-argument-summary-qassim-v-trump
INFO:root:rank=8 pagerank=3.4509e-03 url=www.lawfareblog.com/dc-circuit-court-denies-trump-rehearing-mazars-case
INFO:root:rank=9 pagerank=3.4484e-03 url=www.lawfareblog.com/second-circuit-rules-mazars-must-hand-over-trump-tax-returns-new-york-prosecutors
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --search_query='iran'
INFO:root:rank=0 pagerank=4.5746e-03 url=www.lawfareblog.com/praise-presidents-iran-tweets
INFO:root:rank=1 pagerank=4.4174e-03 url=www.lawfareblog.com/how-us-iran-tensions-could-disrupt-iraqs-fragile-peace
INFO:root:rank=2 pagerank=2.6928e-03 url=www.lawfareblog.com/cyber-command-operational-update-clarifying-june-2019-iran-operation
INFO:root:rank=3 pagerank=1.9391e-03 url=www.lawfareblog.com/aborted-iran-strike-fine-line-between-necessity-and-revenge
INFO:root:rank=4 pagerank=1.5452e-03 url=www.lawfareblog.com/parsing-state-departments-letter-use-force-against-iran
INFO:root:rank=5 pagerank=1.5357e-03 url=www.lawfareblog.com/iranian-hostage-crisis-and-its-effect-american-politics
INFO:root:rank=6 pagerank=1.5258e-03 url=www.lawfareblog.com/announcing-united-states-and-use-force-against-iran-new-lawfare-e-book
INFO:root:rank=7 pagerank=1.4221e-03 url=www.lawfareblog.com/us-names-iranian-revolutionary-guard-terrorist-organization-and-sanctions-international-criminal
INFO:root:rank=8 pagerank=1.1788e-03 url=www.lawfareblog.com/iran-shoots-down-us-drone-domestic-and-international-legal-implications
INFO:root:rank=9 pagerank=1.1463e-03 url=www.lawfareblog.com/israel-iran-syria-clash-and-law-use-force
Part 3:
The webgraph of lawfareblog.com (i.e. the
$ python3 pagerank.py --data=data/lawfareblog.csv.gz
INFO:root:rank=0 pagerank=2.8741e-01 url=www.lawfareblog.com/lawfare-job-board
INFO:root:rank=1 pagerank=2.8741e-01 url=www.lawfareblog.com/masthead
INFO:root:rank=2 pagerank=2.8741e-01 url=www.lawfareblog.com/litigation-documents-related-appointment-matthew-whitaker-acting-attorney-general
INFO:root:rank=3 pagerank=2.8741e-01 url=www.lawfareblog.com/documents-related-mueller-investigation
INFO:root:rank=4 pagerank=2.8741e-01 url=www.lawfareblog.com/topics
INFO:root:rank=5 pagerank=2.8741e-01 url=www.lawfareblog.com/about-lawfare-brief-history-term-and-site
INFO:root:rank=6 pagerank=2.8741e-01 url=www.lawfareblog.com/snowden-revelations
INFO:root:rank=7 pagerank=2.8741e-01 url=www.lawfareblog.com/support-lawfare
INFO:root:rank=8 pagerank=2.8741e-01 url=www.lawfareblog.com/upcoming-events
INFO:root:rank=9 pagerank=2.8741e-01 url=www.lawfareblog.com/our-comments-policy
Most of these pages are not very interesting, however, because they are not articles, and usually when we are performing a web search, we only want articles.
This raises the question: How can we find the most important articles filtering out the non-article pages?
The answer is to modify the
This raises another question: How do we know if a link is a non-article page?
Unfortunately, this is a hard question to answer with 100% accuracy,
but there are many methods that get us most of the way there.
One easy to implement method is to compute what's called the "in-link ratio" of each node (i.e. the total number of edges with the node as a target divided by the total number of nodes),
and then remove nodes from the search results with too-high of a ratio.
The intuition is that non-article pages often appear in the menu of a webpage, and so have links from almost all of the other webpages;
but article-webpages are unlikely to appear on a menu and so will only have a small number of links from other webpages.
The --filter_ratio parameter causes the code to remove all pages that have an in-link ratio larger than the provided value.
Using this option, we can estimate the most important articles on the domain with the following command:
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --filter_ratio=0.2
INFO:root:rank=0 pagerank=3.4696e-01 url=www.lawfareblog.com/trump-asks-supreme-court-stay-congressional-subpeona-tax-returns
INFO:root:rank=1 pagerank=2.9521e-01 url=www.lawfareblog.com/livestream-nov-21-impeachment-hearings-0
INFO:root:rank=2 pagerank=2.9040e-01 url=www.lawfareblog.com/opening-statement-david-holmes
INFO:root:rank=3 pagerank=1.5179e-01 url=www.lawfareblog.com/lawfare-podcast-ben-nimmo-whack-mole-game-disinformation
INFO:root:rank=4 pagerank=1.5099e-01 url=www.lawfareblog.com/todays-headlines-and-commentary-1963
INFO:root:rank=5 pagerank=1.5099e-01 url=www.lawfareblog.com/todays-headlines-and-commentary-1964
INFO:root:rank=6 pagerank=1.5071e-01 url=www.lawfareblog.com/lawfare-podcast-week-was-impeachment
INFO:root:rank=7 pagerank=1.4957e-01 url=www.lawfareblog.com/todays-headlines-and-commentary-1962
INFO:root:rank=8 pagerank=1.4367e-01 url=www.lawfareblog.com/cyberlaw-podcast-mistrusting-google
INFO:root:rank=9 pagerank=1.4240e-01 url=www.lawfareblog.com/lawfare-podcast-bonus-edition-gordon-sondland-vs-committee-no-bull
Notice that the urls in this list look much more like articles than the urls in the previous list.
When Google calculates their
In the case above, notice that we have accidentally removed the blog's most popular article (https://www.lawfareblog.com/snowden-revelations).
The blog editors believed that Snowden's revelations about NSA spying are so important that they directly put a link to the article on the menu.
So every single webpage in the domain links to the Snowden article,
and our "anti-spam" --filter-ratio argument removed this article from the list.
In general, it is a challenging open problem to remove spam from pagerank results,
and all current solutions rely on careful human tuning and still have lots of false positives and false negatives.
Part 4:
Recall from the reading that the runtime of pagerank depends heavily on the eigengap of the
Run the following four commands:
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose --alpha=0.99999
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose --filter_ratio=0.2
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose --filter_ratio=0.2 --alpha=0.99999
You should notice that the last command takes considerably more iterations to compute the pagerank vector. (My code takes 685 iterations for this call, and about 10 iterations for all the others.)
This raises the question: Why does the second command (with the --alpha option but without the --filter_ratio) option not take a long time to run?
The answer is that the
Changing the value of alpha also gives us very different pagerank rankings. For example,
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --filter_ratio=0.2
INFO:root:rank=0 pagerank=3.4696e-01 url=www.lawfareblog.com/trump-asks-supreme-court-stay-congressional-subpeona-tax-returns
INFO:root:rank=1 pagerank=2.9521e-01 url=www.lawfareblog.com/livestream-nov-21-impeachment-hearings-0
INFO:root:rank=2 pagerank=2.9040e-01 url=www.lawfareblog.com/opening-statement-david-holmes
INFO:root:rank=3 pagerank=1.5179e-01 url=www.lawfareblog.com/lawfare-podcast-ben-nimmo-whack-mole-game-disinformation
INFO:root:rank=4 pagerank=1.5099e-01 url=www.lawfareblog.com/todays-headlines-and-commentary-1963
INFO:root:rank=5 pagerank=1.5099e-01 url=www.lawfareblog.com/todays-headlines-and-commentary-1964
INFO:root:rank=6 pagerank=1.5071e-01 url=www.lawfareblog.com/lawfare-podcast-week-was-impeachment
INFO:root:rank=7 pagerank=1.4957e-01 url=www.lawfareblog.com/todays-headlines-and-commentary-1962
INFO:root:rank=8 pagerank=1.4367e-01 url=www.lawfareblog.com/cyberlaw-podcast-mistrusting-google
INFO:root:rank=9 pagerank=1.4240e-01 url=www.lawfareblog.com/lawfare-podcast-bonus-edition-gordon-sondland-vs-committee-no-bull
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --filter_ratio=0.2 --alpha=0.99999
INFO:root:rank=0 pagerank=7.0149e-01 url=www.lawfareblog.com/covid-19-speech-and-surveillance-response
INFO:root:rank=1 pagerank=7.0149e-01 url=www.lawfareblog.com/lawfare-live-covid-19-speech-and-surveillance
INFO:root:rank=2 pagerank=1.0552e-01 url=www.lawfareblog.com/cost-using-zero-days
INFO:root:rank=3 pagerank=3.1755e-02 url=www.lawfareblog.com/lawfare-podcast-former-congressman-brian-baird-and-daniel-schuman-how-congress-can-continue-function
INFO:root:rank=4 pagerank=2.2040e-02 url=www.lawfareblog.com/events
INFO:root:rank=5 pagerank=1.6027e-02 url=www.lawfareblog.com/water-wars-increased-us-focus-indo-pacific
INFO:root:rank=6 pagerank=1.6026e-02 url=www.lawfareblog.com/water-wars-drill-maybe-drill
INFO:root:rank=7 pagerank=1.6023e-02 url=www.lawfareblog.com/water-wars-disjointed-operations-south-china-sea
INFO:root:rank=8 pagerank=1.6020e-02 url=www.lawfareblog.com/water-wars-song-oil-and-fire
INFO:root:rank=9 pagerank=1.6020e-02 url=www.lawfareblog.com/water-wars-sinking-feeling-philippine-china-relations
Which of these rankings is better is entirely subjective, and the only way to know if you have the "best" alpha for your application is to try several variations and see what is best.
NOTE: It should be "obvious" to you that large alpha values imply that the structure of the webgraph has more influence on the final result, and small alpha values ignore the structure of the webgraph. Recall that the word "obvious" means that it follows directly from the definition, but you may still need to sit and meditate on the definition for a long period of time.
If large alphas are good for your application, you can see that there is a trade-off between quality answers and algorithmic runtime. We'll be exploring this trade-off more formally in class over the rest of the semester.
The most interesting applications of pagerank involve the personalization vector.
Implement the WebGraph.make_personalization_vector function so that it outputs a personalization vector tuned for the input query.
The pseudocode for the function is:
for each index in the personalization vector:
get the url for the index (see the _index_to_url function)
check if the url satisfies the input query (see the url_satisfies_query function)
if so, set the corresponding index to one
normalize the vector
Part 1:
The command line argument --personalization_vector_query will use the function you created above to augment your search with a custom personalization vector.
If you've implemented the function correctly,
you should get results similar to:
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --filter_ratio=0.2 --personalization_vector_query='corona'
INFO:root:rank=0 pagerank=6.3127e-01 url=www.lawfareblog.com/covid-19-speech-and-surveillance-response
INFO:root:rank=1 pagerank=6.3124e-01 url=www.lawfareblog.com/lawfare-live-covid-19-speech-and-surveillance
INFO:root:rank=2 pagerank=1.5947e-01 url=www.lawfareblog.com/chinatalk-how-party-takes-its-propaganda-global
INFO:root:rank=3 pagerank=1.2209e-01 url=www.lawfareblog.com/brexit-not-immune-coronavirus
INFO:root:rank=4 pagerank=1.2209e-01 url=www.lawfareblog.com/rational-security-my-corona-edition
INFO:root:rank=5 pagerank=9.3360e-02 url=www.lawfareblog.com/trump-cant-reopen-country-over-state-objections
INFO:root:rank=6 pagerank=9.1920e-02 url=www.lawfareblog.com/prosecuting-purposeful-coronavirus-exposure-terrorism
INFO:root:rank=7 pagerank=9.1920e-02 url=www.lawfareblog.com/britains-coronavirus-response
INFO:root:rank=8 pagerank=7.7770e-02 url=www.lawfareblog.com/lawfare-podcast-united-nations-and-coronavirus-crisis
INFO:root:rank=9 pagerank=7.2888e-02 url=www.lawfareblog.com/house-oversight-committee-holds-day-two-hearing-government-coronavirus-response
Notice that these results are significantly different than when using the --search_query option:
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --filter_ratio=0.2 --search_query='corona'
INFO:root:rank=0 pagerank=8.1320e-03 url=www.lawfareblog.com/house-oversight-committee-holds-day-two-hearing-government-coronavirus-response
INFO:root:rank=1 pagerank=7.7908e-03 url=www.lawfareblog.com/lawfare-podcast-united-nations-and-coronavirus-crisis
INFO:root:rank=2 pagerank=5.2262e-03 url=www.lawfareblog.com/livestream-house-oversight-committee-holds-hearing-government-coronavirus-response
INFO:root:rank=3 pagerank=3.9584e-03 url=www.lawfareblog.com/britains-coronavirus-response
INFO:root:rank=4 pagerank=3.8114e-03 url=www.lawfareblog.com/prosecuting-purposeful-coronavirus-exposure-terrorism
INFO:root:rank=5 pagerank=3.3973e-03 url=www.lawfareblog.com/paper-hearing-experts-debate-digital-contact-tracing-and-coronavirus-privacy-concerns
INFO:root:rank=6 pagerank=3.3633e-03 url=www.lawfareblog.com/cyberlaw-podcast-how-israel-fighting-coronavirus
INFO:root:rank=7 pagerank=3.3557e-03 url=www.lawfareblog.com/israeli-emergency-regulations-location-tracking-coronavirus-carriers
INFO:root:rank=8 pagerank=3.2160e-03 url=www.lawfareblog.com/congress-needs-coronavirus-failsafe-its-too-late
INFO:root:rank=9 pagerank=3.1036e-03 url=www.lawfareblog.com/why-congress-conducting-business-usual-face-coronavirus
Which results are better?
Again, that depends on what you mean by "better."
With the --personalization_vector_query option,
a webpage is important only if other coronavirus webpages also think it's important;
with the --search_query option,
a webpage is important if any other webpage thinks it's important.
You'll notice that in the later example, many of the webpages are about Congressional proceedings related to the coronavirus.
From a strictly coronavirus perspective, these are not very important webpages.
But in the broader context of national security, these are very important webpages.
Google engineers spend TONs of time fine-tuning their pagerank personalization vectors to remove spam webpages. Exactly how they do this is another one of their secrets that they don't publicly talk about.
Part 2:
Another use of the --personalization_vector_query option is that we can find out what webpages are related to the coronavirus but don't directly mention the coronavirus.
This can be used to map out what types of topics are similar to the coronavirus.
For example, the following query ranks all webpages by their corona importance,
but removes webpages mentioning corona from the results.
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --filter_ratio=0.2 --personalization_vector_query='corona' --search_query='-corona'
INFO:root:rank=0 pagerank=6.3127e-01 url=www.lawfareblog.com/covid-19-speech-and-surveillance-response
INFO:root:rank=1 pagerank=6.3124e-01 url=www.lawfareblog.com/lawfare-live-covid-19-speech-and-surveillance
INFO:root:rank=2 pagerank=1.5947e-01 url=www.lawfareblog.com/chinatalk-how-party-takes-its-propaganda-global
INFO:root:rank=3 pagerank=9.3360e-02 url=www.lawfareblog.com/trump-cant-reopen-country-over-state-objections
INFO:root:rank=4 pagerank=7.0277e-02 url=www.lawfareblog.com/fault-lines-foreign-policy-quarantined
INFO:root:rank=5 pagerank=6.9713e-02 url=www.lawfareblog.com/lawfare-podcast-mom-and-dad-talk-clinical-trials-pandemic
INFO:root:rank=6 pagerank=6.4944e-02 url=www.lawfareblog.com/limits-world-health-organization
INFO:root:rank=7 pagerank=5.9492e-02 url=www.lawfareblog.com/chinatalk-dispatches-shanghai-beijing-and-hong-kong
INFO:root:rank=8 pagerank=5.1245e-02 url=www.lawfareblog.com/us-moves-dismiss-case-against-company-linked-ira-troll-farm
INFO:root:rank=9 pagerank=5.1245e-02 url=www.lawfareblog.com/livestream-house-armed-services-holds-hearing-national-security-challenges-north-and-south-america
You can see that there are many urls about concepts that are obviously related like "covid", "clinical trials", and "quarantine", but this algorithm also finds articles about Chinese propaganda and Trump's policy decisions. Both of these articles are highly relevant to coronavirus discussions, but a simple keyword search for corona or related terms would not find these articles. The vast majority of industry data mining work is finding clever uses of standard algorithms.
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Create a new repo on github (not a fork of this repo). Ensure that all of the project files are copied from this folder into your new repo.
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As you complete the tasks above: Run the corresponding commands below, and paste their output into the code blocks. Please ensure correct markdown formatting.
Task 1, part 1:
$ python3 pagerank.py --data=data/small.csv.gz --verbose Arshs-MacBook-Pro-3:PageRankProject arshchhabra$ python3 pagerank.py --data=data/small.csv.gz --verbose DEBUG:root:computing indices DEBUG:root:computing values DEBUG:root:i=0 residual=0.2562914192676544 DEBUG:root:i=1 residual=0.11841227114200592 DEBUG:root:i=2 residual=0.07070134580135345 DEBUG:root:i=3 residual=0.03181542828679085 DEBUG:root:i=4 residual=0.020496590062975883 DEBUG:root:i=5 residual=0.01010835450142622 DEBUG:root:i=6 residual=0.006371544674038887 DEBUG:root:i=7 residual=0.0034227892756462097 DEBUG:root:i=8 residual=0.002087961183860898 DEBUG:root:i=9 residual=0.0011749734403565526 DEBUG:root:i=10 residual=0.0007012754795141518 DEBUG:root:i=11 residual=0.00040320929838344455 DEBUG:root:i=12 residual=0.00023798426263965666 DEBUG:root:i=13 residual=0.00013812065299134701 DEBUG:root:i=14 residual=8.108324982458726e-05 DEBUG:root:i=15 residual=4.7269360948121175e-05 DEBUG:root:i=16 residual=2.7704918466042727e-05 DEBUG:root:i=17 residual=1.6170568414963782e-05 DEBUG:root:i=18 residual=9.479118489252869e-06 DEBUG:root:i=19 residual=5.4782999541203026e-06 DEBUG:root:i=20 residual=3.2123323308042018e-06 DEBUG:root:i=21 residual=1.8802053318722756e-06 DEBUG:root:i=22 residual=1.1228398761886638e-06 DEBUG:root:i=23 residual=6.322027275018627e-07 INFO:root:rank=0 pagerank=6.6270e-01 url=4 INFO:root:rank=1 pagerank=5.2179e-01 url=6 INFO:root:rank=2 pagerank=4.1434e-01 url=5 INFO:root:rank=3 pagerank=2.3175e-01 url=2 INFO:root:rank=4 pagerank=1.8590e-01 url=3 INFO:root:rank=5 pagerank=1.6917e-01 url=1Task 1, part 2:
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --search_query='corona' Arshs-MacBook-Pro-3:PageRankProject arshchhabra$ python3 pagerank.py --data=data/lawfareblog.csv.gz --search_query='corona' INFO:root:rank=0 pagerank=1.0038e-03 url=www.lawfareblog.com/lawfare-podcast-united-nations-and-coronavirus-crisis INFO:root:rank=1 pagerank=8.9228e-04 url=www.lawfareblog.com/house-oversight-committee-holds-day-two-hearing-government-coronavirus-response INFO:root:rank=2 pagerank=7.0394e-04 url=www.lawfareblog.com/britains-coronavirus-response INFO:root:rank=3 pagerank=6.9157e-04 url=www.lawfareblog.com/prosecuting-purposeful-coronavirus-exposure-terrorism INFO:root:rank=4 pagerank=6.7045e-04 url=www.lawfareblog.com/israeli-emergency-regulations-location-tracking-coronavirus-carriers INFO:root:rank=5 pagerank=6.6260e-04 url=www.lawfareblog.com/why-congress-conducting-business-usual-face-coronavirus INFO:root:rank=6 pagerank=6.5050e-04 url=www.lawfareblog.com/congressional-homeland-security-committees-seek-ways-support-state-federal-responses-coronavirus INFO:root:rank=7 pagerank=6.3623e-04 url=www.lawfareblog.com/paper-hearing-experts-debate-digital-contact-tracing-and-coronavirus-privacy-concerns INFO:root:rank=8 pagerank=6.1252e-04 url=www.lawfareblog.com/house-subcommittee-voices-concerns-over-us-management-coronavirus INFO:root:rank=9 pagerank=6.0191e-04 url=www.lawfareblog.com/livestream-house-oversight-committee-holds-hearing-government-coronavirus-response $ python3 pagerank.py --data=data/lawfareblog.csv.gz --search_query='trump' Arshs-MacBook-Pro-3:PageRankProject arshchhabra$ python3 pagerank.py --data=data/lawfareblog.csv.gz --search_query='trump' INFO:root:rank=0 pagerank=5.7827e-03 url=www.lawfareblog.com/trump-asks-supreme-court-stay-congressional-subpeona-tax-returns INFO:root:rank=1 pagerank=5.2340e-03 url=www.lawfareblog.com/document-trump-revokes-obama-executive-order-counterterrorism-strike-casualty-reporting INFO:root:rank=2 pagerank=5.1298e-03 url=www.lawfareblog.com/trump-administrations-worrying-new-policy-israeli-settlements INFO:root:rank=3 pagerank=4.6601e-03 url=www.lawfareblog.com/dc-circuit-overrules-district-courts-due-process-ruling-qasim-v-trump INFO:root:rank=4 pagerank=4.5935e-03 url=www.lawfareblog.com/donald-trump-and-politically-weaponized-executive-branch INFO:root:rank=5 pagerank=4.3073e-03 url=www.lawfareblog.com/how-trumps-approach-middle-east-ignores-past-future-and-human-condition INFO:root:rank=6 pagerank=4.0936e-03 url=www.lawfareblog.com/why-trump-cant-buy-greenland INFO:root:rank=7 pagerank=3.7592e-03 url=www.lawfareblog.com/oral-argument-summary-qassim-v-trump INFO:root:rank=8 pagerank=3.4510e-03 url=www.lawfareblog.com/dc-circuit-court-denies-trump-rehearing-mazars-case INFO:root:rank=9 pagerank=3.4486e-03 url=www.lawfareblog.com/second-circuit-rules-mazars-must-hand-over-trump-tax-returns-new-york-prosecutors $ python3 pagerank.py --data=data/lawfareblog.csv.gz --search_query='iran' Arshs-MacBook-Pro-3:PageRankProject arshchhabra$ python3 pagerank.py --data=data/lawfareblog.csv.gz --search_query='iran' INFO:root:rank=0 pagerank=4.5748e-03 url=www.lawfareblog.com/praise-presidents-iran-tweets INFO:root:rank=1 pagerank=4.4176e-03 url=www.lawfareblog.com/how-us-iran-tensions-could-disrupt-iraqs-fragile-peace INFO:root:rank=2 pagerank=2.6929e-03 url=www.lawfareblog.com/cyber-command-operational-update-clarifying-june-2019-iran-operation INFO:root:rank=3 pagerank=1.9392e-03 url=www.lawfareblog.com/aborted-iran-strike-fine-line-between-necessity-and-revenge INFO:root:rank=4 pagerank=1.5453e-03 url=www.lawfareblog.com/parsing-state-departments-letter-use-force-against-iran INFO:root:rank=5 pagerank=1.5358e-03 url=www.lawfareblog.com/iranian-hostage-crisis-and-its-effect-american-politics INFO:root:rank=6 pagerank=1.5258e-03 url=www.lawfareblog.com/announcing-united-states-and-use-force-against-iran-new-lawfare-e-book INFO:root:rank=7 pagerank=1.4222e-03 url=www.lawfareblog.com/us-names-iranian-revolutionary-guard-terrorist-organization-and-sanctions-international-criminal INFO:root:rank=8 pagerank=1.1788e-03 url=www.lawfareblog.com/iran-shoots-down-us-drone-domestic-and-international-legal-implications INFO:root:rank=9 pagerank=1.1463e-03 url=www.lawfareblog.com/israel-iran-syria-clash-and-law-use-forceTask 1, part 3:
$ python3 pagerank.py --data=data/lawfareblog.csv.gz Arshs-MacBook-Pro-3:PageRankProject arshchhabra$ python3 pagerank.py --data=data/lawfareblog.csv.gz INFO:root:rank=0 pagerank=2.8741e-01 url=www.lawfareblog.com/about-lawfare-brief-history-term-and-site INFO:root:rank=1 pagerank=2.8741e-01 url=www.lawfareblog.com/lawfare-job-board INFO:root:rank=2 pagerank=2.8741e-01 url=www.lawfareblog.com/masthead INFO:root:rank=3 pagerank=2.8741e-01 url=www.lawfareblog.com/litigation-documents-resources-related-travel-ban INFO:root:rank=4 pagerank=2.8741e-01 url=www.lawfareblog.com/subscribe-lawfare INFO:root:rank=5 pagerank=2.8741e-01 url=www.lawfareblog.com/litigation-documents-related-appointment-matthew-whitaker-acting-attorney-general INFO:root:rank=6 pagerank=2.8741e-01 url=www.lawfareblog.com/documents-related-mueller-investigation INFO:root:rank=7 pagerank=2.8741e-01 url=www.lawfareblog.com/our-comments-policy INFO:root:rank=8 pagerank=2.8741e-01 url=www.lawfareblog.com/upcoming-events INFO:root:rank=9 pagerank=2.8741e-01 url=www.lawfareblog.com/topics $ python3 pagerank.py --data=data/lawfareblog.csv.gz --filter_ratio=0.2 Arshs-MacBook-Pro-3:PageRankProject arshchhabra$ python3 pagerank.py --data=data/lawfareblog.csv.gz --filter_ratio=0.2 INFO:root:rank=0 pagerank=3.4697e-01 url=www.lawfareblog.com/trump-asks-supreme-court-stay-congressional-subpeona-tax-returns INFO:root:rank=1 pagerank=2.9522e-01 url=www.lawfareblog.com/livestream-nov-21-impeachment-hearings-0 INFO:root:rank=2 pagerank=2.9040e-01 url=www.lawfareblog.com/opening-statement-david-holmes INFO:root:rank=3 pagerank=1.5179e-01 url=www.lawfareblog.com/lawfare-podcast-ben-nimmo-whack-mole-game-disinformation INFO:root:rank=4 pagerank=1.5100e-01 url=www.lawfareblog.com/todays-headlines-and-commentary-1964 INFO:root:rank=5 pagerank=1.5100e-01 url=www.lawfareblog.com/todays-headlines-and-commentary-1963 INFO:root:rank=6 pagerank=1.5072e-01 url=www.lawfareblog.com/lawfare-podcast-week-was-impeachment INFO:root:rank=7 pagerank=1.4958e-01 url=www.lawfareblog.com/todays-headlines-and-commentary-1962 INFO:root:rank=8 pagerank=1.4367e-01 url=www.lawfareblog.com/cyberlaw-podcast-mistrusting-google INFO:root:rank=9 pagerank=1.4240e-01 url=www.lawfareblog.com/lawfare-podcast-bonus-edition-gordon-sondland-vs-committee-no-bullTask 1, part 4:
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose Arshs-MacBook-Pro-3:PageRankProject arshchhabra$ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose DEBUG:root:computing indices DEBUG:root:computing values DEBUG:root:i=0 residual=1.3793749809265137 DEBUG:root:i=1 residual=0.11642683297395706 DEBUG:root:i=2 residual=0.07496178895235062 DEBUG:root:i=3 residual=0.031702104955911636 DEBUG:root:i=4 residual=0.0174466110765934 DEBUG:root:i=5 residual=0.008526231162250042 DEBUG:root:i=6 residual=0.00444182800129056 DEBUG:root:i=7 residual=0.0022433267440646887 DEBUG:root:i=8 residual=0.001149666146375239 DEBUG:root:i=9 residual=0.0005811726441606879 DEBUG:root:i=10 residual=0.00029266104684211314 DEBUG:root:i=11 residual=0.00014553753135260195 DEBUG:root:i=12 residual=7.151532918214798e-05 DEBUG:root:i=13 residual=3.476878555375151e-05 DEBUG:root:i=14 residual=1.5952729881973937e-05 DEBUG:root:i=15 residual=6.454707545344718e-06 DEBUG:root:i=16 residual=2.470087110850727e-06 DEBUG:root:i=17 residual=8.236708595177333e-07 INFO:root:rank=0 pagerank=2.8741e-01 url=www.lawfareblog.com/about-lawfare-brief-history-term-and-site INFO:root:rank=1 pagerank=2.8741e-01 url=www.lawfareblog.com/lawfare-job-board INFO:root:rank=2 pagerank=2.8741e-01 url=www.lawfareblog.com/masthead INFO:root:rank=3 pagerank=2.8741e-01 url=www.lawfareblog.com/litigation-documents-resources-related-travel-ban INFO:root:rank=4 pagerank=2.8741e-01 url=www.lawfareblog.com/subscribe-lawfare INFO:root:rank=5 pagerank=2.8741e-01 url=www.lawfareblog.com/litigation-documents-related-appointment-matthew-whitaker-acting-attorney-general INFO:root:rank=6 pagerank=2.8741e-01 url=www.lawfareblog.com/documents-related-mueller-investigation INFO:root:rank=7 pagerank=2.8741e-01 url=www.lawfareblog.com/our-comments-policy INFO:root:rank=8 pagerank=2.8741e-01 url=www.lawfareblog.com/upcoming-events INFO:root:rank=9 pagerank=2.8741e-01 url=www.lawfareblog.com/topics $ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose --alpha=0.99999 Arshs-MacBook-Pro-3:PageRankProject arshchhabra$ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose --alpha=0.99999 DEBUG:root:computing indices DEBUG:root:computing values DEBUG:root:i=0 residual=1.384641170501709 DEBUG:root:i=1 residual=0.07088145613670349 DEBUG:root:i=2 residual=0.01882273517549038 DEBUG:root:i=3 residual=0.006958308629691601 DEBUG:root:i=4 residual=0.0027358275838196278 DEBUG:root:i=5 residual=0.0010345610789954662 DEBUG:root:i=6 residual=0.0003774643409997225 DEBUG:root:i=7 residual=0.0001353343395749107 DEBUG:root:i=8 residual=4.822430855710991e-05 DEBUG:root:i=9 residual=1.717166742309928e-05 DEBUG:root:i=10 residual=6.1166115301602986e-06 DEBUG:root:i=11 residual=2.1727698822360253e-06 DEBUG:root:i=12 residual=7.75930004692782e-07 INFO:root:rank=0 pagerank=2.8859e-01 url=www.lawfareblog.com/snowden-revelations INFO:root:rank=1 pagerank=2.8859e-01 url=www.lawfareblog.com/lawfare-job-board INFO:root:rank=2 pagerank=2.8859e-01 url=www.lawfareblog.com/documents-related-mueller-investigation INFO:root:rank=3 pagerank=2.8859e-01 url=www.lawfareblog.com/litigation-documents-resources-related-travel-ban INFO:root:rank=4 pagerank=2.8859e-01 url=www.lawfareblog.com/subscribe-lawfare INFO:root:rank=5 pagerank=2.8859e-01 url=www.lawfareblog.com/topics INFO:root:rank=6 pagerank=2.8859e-01 url=www.lawfareblog.com/masthead INFO:root:rank=7 pagerank=2.8859e-01 url=www.lawfareblog.com/our-comments-policy INFO:root:rank=8 pagerank=2.8859e-01 url=www.lawfareblog.com/upcoming-events INFO:root:rank=9 pagerank=2.8859e-01 url=www.lawfareblog.com/litigation-documents-related-appointment-matthew-whitaker-acting-attorney-general $ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose --filter_ratio=0.2 Arshs-MacBook-Pro-3:PageRankProject arshchhabra$ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose --filter_ratio=0.2 DEBUG:root:computing indices DEBUG:root:computing values DEBUG:root:i=0 residual=1.2609769105911255 DEBUG:root:i=1 residual=0.4985710680484772 DEBUG:root:i=2 residual=0.13418613374233246 DEBUG:root:i=3 residual=0.0692228302359581 DEBUG:root:i=4 residual=0.023409796878695488 DEBUG:root:i=5 residual=0.010187179781496525 DEBUG:root:i=6 residual=0.00490697892382741 DEBUG:root:i=7 residual=0.002280232962220907 DEBUG:root:i=8 residual=0.0010745070176199079 DEBUG:root:i=9 residual=0.0005251269903965294 DEBUG:root:i=10 residual=0.00026976881781592965 DEBUG:root:i=11 residual=0.00014569450286217034 DEBUG:root:i=12 residual=8.226578938774765e-05 DEBUG:root:i=13 residual=4.813347550225444e-05 DEBUG:root:i=14 residual=2.8801283406210132e-05 DEBUG:root:i=15 residual=1.7420436051907018e-05 DEBUG:root:i=16 residual=1.0539955837884918e-05 DEBUG:root:i=17 residual=6.396006028808188e-06 DEBUG:root:i=18 residual=3.848239430226386e-06 DEBUG:root:i=19 residual=2.298697609148803e-06 DEBUG:root:i=20 residual=1.3677324659511214e-06 DEBUG:root:i=21 residual=8.154062811627227e-07 INFO:root:rank=0 pagerank=3.4697e-01 url=www.lawfareblog.com/trump-asks-supreme-court-stay-congressional-subpeona-tax-returns INFO:root:rank=1 pagerank=2.9522e-01 url=www.lawfareblog.com/livestream-nov-21-impeachment-hearings-0 INFO:root:rank=2 pagerank=2.9040e-01 url=www.lawfareblog.com/opening-statement-david-holmes INFO:root:rank=3 pagerank=1.5179e-01 url=www.lawfareblog.com/lawfare-podcast-ben-nimmo-whack-mole-game-disinformation INFO:root:rank=4 pagerank=1.5100e-01 url=www.lawfareblog.com/todays-headlines-and-commentary-1964 INFO:root:rank=5 pagerank=1.5100e-01 url=www.lawfareblog.com/todays-headlines-and-commentary-1963 INFO:root:rank=6 pagerank=1.5072e-01 url=www.lawfareblog.com/lawfare-podcast-week-was-impeachment INFO:root:rank=7 pagerank=1.4958e-01 url=www.lawfareblog.com/todays-headlines-and-commentary-1962 INFO:root:rank=8 pagerank=1.4367e-01 url=www.lawfareblog.com/cyberlaw-podcast-mistrusting-google INFO:root:rank=9 pagerank=1.4240e-01 url=www.lawfareblog.com/lawfare-podcast-bonus-edition-gordon-sondland-vs-committee-no-bull $ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose --filter_ratio=0.2 --alpha=0.99999 Arshs-MacBook-Pro-3:PageRankProject arshchhabra$ python3 pagerank.py --data=data/lawfareblog.csv.gz --verbose --filter_ratio=0.2 --alpha=0.99999 DEBUG:root:computing indices DEBUG:root:computing values DEBUG:root:i=0 residual=1.2827692031860352 DEBUG:root:i=1 residual=0.5695649981498718 DEBUG:root:i=2 residual=0.382994681596756 DEBUG:root:i=3 residual=0.21739362180233002 DEBUG:root:i=4 residual=0.140450581908226 DEBUG:root:i=5 residual=0.1085134968161583 DEBUG:root:i=6 residual=0.09284142404794693 DEBUG:root:i=7 residual=0.08225550502538681 DEBUG:root:i=8 residual=0.07338894158601761 DEBUG:root:i=9 residual=0.06561233103275299 DEBUG:root:i=10 residual=0.0590965561568737 DEBUG:root:i=11 residual=0.05417540296912193 DEBUG:root:i=12 residual=0.0511169508099556 DEBUG:root:i=13 residual=0.04999380558729172 DEBUG:root:i=14 residual=0.05060896649956703 DEBUG:root:i=15 residual=0.05252620205283165 DEBUG:root:i=16 residual=0.05518876016139984 DEBUG:root:i=17 residual=0.05803852155804634 DEBUG:root:i=18 residual=0.06059242784976959 DEBUG:root:i=19 residual=0.06247842311859131 DEBUG:root:i=20 residual=0.06345325708389282 DEBUG:root:i=21 residual=0.06340522319078445 DEBUG:root:i=22 residual=0.06234562769532204 DEBUG:root:i=23 residual=0.06038373336195946 DEBUG:root:i=24 residual=0.057693902403116226 DEBUG:root:i=25 residual=0.05447976663708687 DEBUG:root:i=26 residual=0.05094278231263161 DEBUG:root:i=27 residual=0.04726114124059677 DEBUG:root:i=28 residual=0.043578632175922394 DEBUG:root:i=29 residual=0.04000166058540344 DEBUG:root:i=30 residual=0.03660226985812187 DEBUG:root:i=31 residual=0.03342437744140625 DEBUG:root:i=32 residual=0.030489342287182808 DEBUG:root:i=33 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residual=1.206725414704124e-06 DEBUG:root:i=668 residual=1.1934091617149534e-06 DEBUG:root:i=669 residual=1.1815344578280929e-06 DEBUG:root:i=670 residual=1.167345203612058e-06 DEBUG:root:i=671 residual=1.1580368663999252e-06 DEBUG:root:i=672 residual=1.1442798495409079e-06 DEBUG:root:i=673 residual=1.131452108893427e-06 DEBUG:root:i=674 residual=1.1185842367922305e-06 DEBUG:root:i=675 residual=1.1070404752899776e-06 DEBUG:root:i=676 residual=1.0923960189757054e-06 DEBUG:root:i=677 residual=1.096402002076502e-06 DEBUG:root:i=678 residual=1.0742927543105907e-06 DEBUG:root:i=679 residual=1.060759245774534e-06 DEBUG:root:i=680 residual=1.0497816447241348e-06 DEBUG:root:i=681 residual=1.038765049088397e-06 DEBUG:root:i=682 residual=1.0268878440911067e-06 DEBUG:root:i=683 residual=1.021697585201764e-06 DEBUG:root:i=684 residual=1.0035560080723371e-06 DEBUG:root:i=685 residual=9.938793255059863e-07 INFO:root:rank=0 pagerank=7.0149e-01 url=www.lawfareblog.com/covid-19-speech-and-surveillance-response INFO:root:rank=1 pagerank=7.0149e-01 url=www.lawfareblog.com/lawfare-live-covid-19-speech-and-surveillance INFO:root:rank=2 pagerank=1.0552e-01 url=www.lawfareblog.com/cost-using-zero-days INFO:root:rank=3 pagerank=3.1757e-02 url=www.lawfareblog.com/lawfare-podcast-former-congressman-brian-baird-and-daniel-schuman-how-congress-can-continue-function INFO:root:rank=4 pagerank=2.2040e-02 url=www.lawfareblog.com/events INFO:root:rank=5 pagerank=1.6027e-02 url=www.lawfareblog.com/water-wars-increased-us-focus-indo-pacific INFO:root:rank=6 pagerank=1.6026e-02 url=www.lawfareblog.com/water-wars-drill-maybe-drill INFO:root:rank=7 pagerank=1.6023e-02 url=www.lawfareblog.com/water-wars-disjointed-operations-south-china-sea INFO:root:rank=8 pagerank=1.6020e-02 url=www.lawfareblog.com/water-wars-song-oil-and-fire INFO:root:rank=9 pagerank=1.6020e-02 url=www.lawfareblog.com/water-wars-sinking-feeling-philippine-china-relationsTask 2, part 1:
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --filter_ratio=0.2 --personalization_vector_query='corona' Arshs-MacBook-Pro-3:PageRankProject arshchhabra$ python3 pagerank.py --data=data/lawfareblog.csv.gz --filter_ratio=0.2 --personalization_vector_query='corona' INFO:root:rank=0 pagerank=6.3127e-01 url=www.lawfareblog.com/covid-19-speech-and-surveillance-response INFO:root:rank=1 pagerank=6.3124e-01 url=www.lawfareblog.com/lawfare-live-covid-19-speech-and-surveillance INFO:root:rank=2 pagerank=1.5947e-01 url=www.lawfareblog.com/chinatalk-how-party-takes-its-propaganda-global INFO:root:rank=3 pagerank=1.2209e-01 url=www.lawfareblog.com/brexit-not-immune-coronavirus INFO:root:rank=4 pagerank=1.2209e-01 url=www.lawfareblog.com/rational-security-my-corona-edition INFO:root:rank=5 pagerank=9.3360e-02 url=www.lawfareblog.com/trump-cant-reopen-country-over-state-objections INFO:root:rank=6 pagerank=9.1920e-02 url=www.lawfareblog.com/prosecuting-purposeful-coronavirus-exposure-terrorism INFO:root:rank=7 pagerank=9.1920e-02 url=www.lawfareblog.com/britains-coronavirus-response INFO:root:rank=8 pagerank=7.7770e-02 url=www.lawfareblog.com/lawfare-podcast-united-nations-and-coronavirus-crisis INFO:root:rank=9 pagerank=7.2888e-02 url=www.lawfareblog.com/house-oversight-committee-holds-day-two-hearing-government-coronavirus-responseTask 2, part 2:
$ python3 pagerank.py --data=data/lawfareblog.csv.gz --filter_ratio=0.2 --personalization_vector_query='corona' --search_query='-corona' Arshs-MacBook-Pro-3:PageRankProject arshchhabra$ python3 pagerank.py --data=data/lawfareblog.csv.gz --filter_ratio=0.2 --personalization_vector_query='corona' --search_query='-corona' INFO:root:rank=0 pagerank=6.3127e-01 url=www.lawfareblog.com/covid-19-speech-and-surveillance-response INFO:root:rank=1 pagerank=6.3124e-01 url=www.lawfareblog.com/lawfare-live-covid-19-speech-and-surveillance INFO:root:rank=2 pagerank=1.5947e-01 url=www.lawfareblog.com/chinatalk-how-party-takes-its-propaganda-global INFO:root:rank=3 pagerank=9.3360e-02 url=www.lawfareblog.com/trump-cant-reopen-country-over-state-objections INFO:root:rank=4 pagerank=7.0277e-02 url=www.lawfareblog.com/fault-lines-foreign-policy-quarantined INFO:root:rank=5 pagerank=6.9713e-02 url=www.lawfareblog.com/lawfare-podcast-mom-and-dad-talk-clinical-trials-pandemic INFO:root:rank=6 pagerank=6.4944e-02 url=www.lawfareblog.com/limits-world-health-organization INFO:root:rank=7 pagerank=5.9492e-02 url=www.lawfareblog.com/chinatalk-dispatches-shanghai-beijing-and-hong-kong INFO:root:rank=8 pagerank=5.1245e-02 url=www.lawfareblog.com/us-moves-dismiss-case-against-company-linked-ira-troll-farm INFO:root:rank=9 pagerank=5.1245e-02 url=www.lawfareblog.com/livestream-house-armed-services-committee-holds-hearing-priorities-missile-defense -
Ensure that all your changes to the
pagerank.pyandREADME.mdfiles are committed to your repo and pushed to github. -
Get at least 5 stars on your repo. (You may trade stars with other students in the class.)
NOTE:
Recruiters use github profiles to determine who to hire, and pagerank is used to rank user profiles and projects. Links in this graph correspond to who has starred/followed who's repo. By getting more stars on your repo, you'll be increasing your github pagerank, which increases the likelihood that recruiters will hire you. To see an example, perform a search for
data mining. Notice that the results are returned "approximately" ranked by the number of stars, but because "some stars count more than others" the results are not exactly ranked by the number of stars. (I asked you not to fork this repo because forks are ranked lower than non-forks.)In some sense, we are doing a "dual problem" to data mining by getting these stars. Recruiters are using data mining to find out who the best people to recruit are, and we are hacking their data mining algorithms by making those algorithms select you instead of someone else.
If you're interested in exploring this idea further, here's a python tutorial for extracting GitHub's social graph: https://www.oreilly.com/library/view/mining-the-social/9781449368180/ch07.html ; if you're interested in learning more about how recruiters use github profiles, read this Hacker News post: https://news.ycombinator.com/item?id=19413348.
-
Submit the url of your repo to sakai.
The assignment is worth 8 points.
- There are 6 parts to the output above. (4 in Task1 and 2 in Task2.)
- Each part that you get incorrect will result in -2 points. (But you cannot go negative.)
- Another way of phrasing this is that the first 2 parts you complete are not worth any points, but each part after that is worth 2 points.