FAQ

Frequently Asked Questions

Creating Fake Relationship Profiles for Facts Research

Creating Fake Relationship Profiles for Facts Research

Forging Relationships Users for Facts Analysis by Webscraping

Feb 21, 2020 · 5 minute study

D ata is amongst the world’s new and most precious tools. This facts can include a person’s browsing habits, economic facts, or passwords. Regarding companies concentrated on matchmaking for example Tinder or Hinge, this facts have a user’s personal data they voluntary disclosed with regards to their online dating profiles. Thanks to this inescapable fact, this info are kept private making inaccessible with the community.

However, can you imagine we wanted to generate a venture that utilizes this type of data? If we planned to write an innovative new dating application that uses equipment understanding and man-made cleverness, we’d require a large amount of facts that belongs to these firms. However these providers understandably keep their unique user’s facts exclusive and off the public. So just how would we manage these types of a job?

Well, based on the shortage of individual details in dating profiles, we’d must create phony individual ideas for internet dating profiles. We truly need this forged data so that you can attempt to use equipment training for our internet dating program. Today the origin with the tip because of this application could be read about in the previous post:

Implementing Machine Teaching Themselves To Discover Love

The most important Stages In Developing an AI Matchmaker

The earlier article handled the design or format of your prospective matchmaking application. We might incorporate a device learning formula also known as K-Means Clustering to cluster each dating profile centered on their particular solutions or choices for a number of categories. Furthermore, we create take into account whatever they discuss in their bio as another factor that performs a component in clustering the users. The theory behind this format is that people, in general, are far more appropriate for other individuals who discuss their particular same philosophy ( politics, religion) and passion ( sporting events, films, etc.).

Because of the matchmaking software idea in mind, we could begin gathering or forging the fake visibility facts to nourish into our device mastering algorithm. If something such as it has already been fdating made before, then at the very least we would discovered a little about normal code control ( NLP) and unsupervised learning in K-Means Clustering.

First thing we’d should do is to look for a method to develop an artificial bio for each report. There is no possible solution to create 1000s of artificial bios in an acceptable amount of time. In order to construct these artificial bios, we are going to need to depend on a 3rd party website that will establish phony bios for us. There are several web sites nowadays which will build fake profiles for people. But we won’t getting revealing the website your option due to the fact that I will be implementing web-scraping method.

Making use of BeautifulSoup

I will be using BeautifulSoup to navigate the artificial bio generator websites to scrape multiple different bios produced and put all of them into a Pandas DataFrame. This can allow us to manage to refresh the web page many times in order to create the mandatory amount of phony bios for the internet dating pages.

The initial thing we perform are transfer all the required libraries for all of us to perform our web-scraper. We will be detailing the exceptional collection solutions for BeautifulSoup to run effectively such as for example:

  • demands we can access the website we have to scrape.
  • energy will likely be needed being waiting between website refreshes.
  • tqdm is only necessary as a running club in regards to our benefit.
  • bs4 will become necessary to be able to make use of BeautifulSoup.

Scraping the Webpage

The second part of the laws entails scraping the website when it comes down to user bios. The first thing we make is actually a listing of rates ranging from 0.8 to 1.8. These data represent the number of moments I will be waiting to recharge the page between requests. The next thing we make was a vacant listing to keep every bios we will be scraping from the page.

Then, we establish a cycle that can replenish the page 1000 hours so that you can build the sheer number of bios we wish (which can be around 5000 different bios). The cycle is actually wrapped around by tqdm to be able to write a loading or progress bar to exhibit you how much time are kept in order to complete scraping this site.

Knowledgeable, we make use of desires to access the webpage and retrieve their material. The attempt declaration can be used because sometimes refreshing the website with demands profits nothing and would cause the rule to fail. In those situations, we will just simply pass to a higher loop. Inside consider declaration is where we really fetch the bios and create them to the empty record we formerly instantiated. After accumulating the bios in the current web page, we need time.sleep(random.choice(seq)) to ascertain how much time to attend until we start the next loop. This is done to ensure that our refreshes tend to be randomized considering arbitrarily selected time-interval from your list of numbers.

As we have the ability to the bios necessary through the web site, we will transform the menu of the bios into a Pandas DataFrame.

To complete the artificial dating pages, we are going to must complete another categories of religion, government, flicks, shows, etc. This after that component really is easy as it does not require all of us to web-scrape things. In essence, we are generating a listing of arbitrary rates to utilize to every classification.

First thing we carry out are set up the groups in regards to our online dating pages. These groups include next put into a list subsequently changed into another Pandas DataFrame. Next we are going to iterate through each brand-new line we created and use numpy to generate a random quantity starting from 0 to 9 for every row. The sheer number of rows will depend on the total amount of bios we were in a position to retrieve in the previous DataFrame.

As we possess haphazard data each classification, we are able to get in on the Bio DataFrame while the classification DataFrame collectively to perform the data in regards to our fake relationships users. Eventually, we are able to export the last DataFrame as a .pkl apply for later need.

Since just about everyone has the information for our phony relationships profiles, we could start examining the dataset we just produced. Making use of NLP ( All-natural words running), we will be capable grab a detailed go through the bios for every dating visibility. After some exploration of the data we can really began modeling making use of K-Mean Clustering to complement each visibility with one another. Watch for the following post that may manage utilizing NLP to understand more about the bios and maybe K-Means Clustering at the same time.

What is Telemedicine?

Telemedicine is a service which allows health care professionals to evaluate, diagnose and treat patients using telecommunications technology.

Why should I use GoLiveDoc?

GoLiveDoc offers 24/7 medical consultations with board-certified doctors. You can use our platform from where you live, work or when you travel in the US. We also offer 24/7 behavioral health counseling for no additional fee. Health records are kept private and secure in order to protect your personal information.

How does GoLiveDoc Help?

GoLiveDoc gives you 24/7 access to board-certified doctors through secure online video or phone consultations – anytime, anywhere. GoLiveDoc is a low-cost, convenient alternativ e to Urgent Care visits or waiting several days to get an appointment with your Primary Care Physician for non- emergency medical conditions. Our doctors can diagnose your symptoms, recommend treatment […]

What happens after I complete the checkout process?

Once you have selected your plan and completed the checkout process, you will receive an email with your login credentials for the customer portal. You can use the customer portal to schedule appointments, update your electronic health records, see your consultation history or add dependents to your account.

How much does GoLiveDoc Cost?

The monthly membership fee ranges from $9.95 to $39.95 (depending on the plan you choose). The consultation fee is only $35. You can cancel your membership at any time for any reason.

If I have insurance, do I still need to pay the membership fee?

GoLiveDoc charges all members a small monthly fee.

How do I cancel my membership?

You can cancel your membership at any time for any reason. To cancel your membership, please call (888) 386-1037 or send an email to [email protected]

Does a patient have to meet with a provider in-person before a telemedicine consultation can be scheduled?

No, an in-person visit is not required before a visit can be conducted via telephone or video.

What does GoLiveDoc Treat?

We treat a variety of medical conditions. Common conditions we prescribe medication for are Cold & Flu, Pink Eye, Skin Irritation/Rash, Urinary Tract Infection, Diarrhea, Stomach Virus, Fever, Headaches and Sore Throat.

Are there Medical Conditions GoLiveDoc Cannot Treat?

There are some medical conditions that our doctors are unable to treat, including but not limited to: Broken Bones, Chronic Diseases, Erectile Dysfunction, Genital Herpes, Hair Loss, Hot Flashes, Premature Ejacuation, Smoking Cessation, STD Testing.

Can I be turned down for a pre-existing condition?

No, members are not turned away because of pre-existing conditions. GoLiveDoc is not an insurance.

Can GoLiveDoc Treat Emergencies?

GoLiveDoc Is Only For Non-Emergency Medical Issues Members Should Not Use It If They Are Experiencing A Medical Emergency. Please Dial 911 If You Are Having A Medical Emergency. GoLiveDoc Is Also Not Intended To Replace A Member’s Primary Care Physician.

Is GoLiveDoc For Emergency Situations?

GoLiveDoc Is Only For Non-Emergency Medical Issues Members Should Not Use It If They Are Experiencing A Medical Emergency. Please Dial 911 If You Are Having A Medical Emergency. GoLiveDoc Is Also Not Intended To Replace A Member’s Primary Care Physician.

Can I use it for my family?

The primary member and 7 immediate family members or household members will have access to consults. 

Do I talk to “real doctors”?

Yes. Members only talk to actual doctors who are state-licensed family practitioners, primary care physicians, internists and pediatricians. When members request a consult, they will be connected with a doctor licensed and practicing in their state.

What Type Of Doctor Or Specialist Can I Speak With?

Members Can Talk To A Doctor Directly. Our Doctors Are Licensed In Internal Medicine, Family Medicine And Pediatrics. A Doctor May Also Provide Guidance On The Type Of Specialist A Member Should See.

Can GoLiveDoc prescribe medications?

Yes, GoLiveDoc can prescribe medication for non-controlled substances. A list of controlled substances can be found here.

Are there Medications GoLiveDoc Cannot Prescribe?

We do not prescribe controlled substances and medications that would require in-person examinations, e.g. Antidepressants, birth control, medical marijuana, stimulants such as Adderall and Ritalin, narcotics or sedatives. Our Counselors cannot prescribe medications for mental health purposes.

Does GoLiveDoc Offer Access To Mental Health Professionals?

All Membership Plans Include 24/7 Behavioral And Mental Health Counseling. All Of Our Counselors Have A Master’s Degree And At Least 12 Years Of Experience.

Is there an extra fee to access mental health professionals?

There is no additional fee to speak with mental health professionals.

How does GoLiveDoc handle bloodwork, imaging, labs and other tests?

You can upload all bloodwork, imaging, labs and other tests to our secured portal for our doctors to view to help with diagnosing and treating your medical conditions.

Is My Electronic Health Record Kept Private?

Health Records Are Kept Private And Secure In Order To Protect Members’ Personal Information. Only Members Can Determine Who Can See The Information In Their Records.