I am setting up a basic order in Google Ad Manager- it is for a pharma company and they have an extensive list of negative keywords and prohibit their ads being served on pages where those keywords exist. I would like to apply these keywords to their order, and I found some info on "labels," which I set up, but I am unsure how to apply those to the order to indicate the negative context, or if this is even the correct method to do so!
I found some info on "labels," which I set up, but I am unsure how to apply those to the order to indicate the negative context.
Related
I am working on a project that involves integrating the PUBG API. From my site, the player can lookup stats using their player name, platform and season. One issue I am facing is that the player name have to be exact and is case sensitive. Now I assumed it to be the case at the beginning. However, after searching for the name in this site I found that they don't need the name to be case sensitive. Also, referring to this post from the PUBG Dev community here I saw that it confirmed my initial assumption. So my question is if PUBG API requires the names to be case sensitive then, how is the site (linked) can search for the player even if the name provided is not in exact, matching case? For example,:
I looked up the player name MyCholula. From the PUBG API page for player lookup, it returns the proper value. When I tried mycholula, it doesn't and sends a 404. From the linked site above, both combination seems to work. Now if spaces or other separators were involved in the name then, it would be easy to convert it assuming that separated words are all capitalized (somewhat naive assumption though). For this name, I don't see any way of converting mycholula to MyCholula. I also tried many other combination in the linked site above (also different user names I got from my friends) to confirm that the linked site is actually returning the data as expected for any combination of user names. I also tried it on other sites like this and it didn't work just like it doesn't work from the PUBG DEV API page or from my page.
I am really confused as to how they are doing it. The only possible explanation I can come up with is that they have the player records stored in their database from where, they can perform advanced regexp based search to get the actual name. However, this sounds far fetched since, there are millions of players and it would require them to know all the player names and associated IDs. Also, as far as I know, it is not possible to use regex or other string manipulation to convert to the actual name because there can be many combinations (not an expert on regex so can't be definitive on this).
Any help or suggestions will be greatly appreciated. Thanks.
I am working with the Google Ads team in my company on a Shopify store and they asked me for some regular expressions for the several steps of the checkout process. I created them and everything was running fine, until the guys noticed that sometimes Analytics added a _ga paremeter to the URL query parameters.
My original expressions are:
1. When in cart - no problem here
\/cart
2. First step of checkout - Contact Information - In several lines for easier reading
(
\/([0-9]*)\/checkouts\/([a-z0-9\-]*)$
|
\/([0-9]*)\/checkouts\/([a-z0-9\-]*)\?step=contact_information
)
In this part I added the step=contact_information as an OR option. It isn't normally there except for when you go back to contact information it is added to the URL as step. I know this is not the ideal way, but I am far from fluent in regex.
3. Shipping information
(
\/([0-9]*)\/checkouts\/([a-z0-9\-]*)\?step=shipping_method
|
\/([0-9]*)\/checkouts\/([a-z0-9\-]*)?(.*)&step=shipping_method
)
In this part it always has step=shipping_method but it can also have previous_step=contact_information. This is also not ideal, but I am not sure how to do it.
4. Payment information
(
\/([0-9]*)\/checkouts\/([a-z0-9\-]*)\?step=payment_method
|
\/([0-9]*)\/checkouts\/([a-z0-9\-]*)?(.*)&step=payment_method
)
The same as step 3, in this case it always has step=payment_method but it can also have previous_step=shipping_method. As points 2 and 3, not ideal.
5. Processing - this part works fine, because I am not interested in the query parameters
\/([0-9]*)\/checkouts\/([a-z0-9\-]*)\/processing
6. Thank you page - this also works fine, because I am not interested in the query parameters
\/([0-9]*)\/checkouts\/([a-z0-9\-]*)\/thank_you
Issue with _ga parameter
Those regular expressions work fine with the regular URLs, but when I add the _ga parameter to the URL they don't match. I think there was a way to match query parameters, but I am not sure how to match certain and exclude others.
The _ga parameter normally persists on the next steps
The list of all the possible matches for points 2., 3. and 4.:
Contact information without and with _ga
/25931284564/checkouts/df24e48ecc81f767583c4a26680bcb82
/25931284564/checkouts/df24e48ecc81f767583c4a26680bcb82?step=contact_information
/25931284564/checkouts/df24e48ecc81f767583c4a26680bcb82?_ga=2.150710640.738515769.1576779089-71346777.1571176760%26_gac%3D1.16451458.1576260301.EAIaIQobChMI9v2c5Zqz5gIVr__jBx1VAgxPEAAYBCAAEgLccPD_BwE&locale=es
/25931284564/checkouts/df24e48ecc81f767583c4a26680bcb82?_ga=2.150710640.738515769.1576779089-71346777.1571176760%26_gac%3D1.16451458.1576260301.EAIaIQobChMI9v2c5Zqz5gIVr__jBx1VAgxPEAAYBCAAEgLccPD_BwE&locale=es&step=contact_information
Shipping method without and with _ga
/25931284564/checkouts/df24e48ecc81f767583c4a26680bcb82?step=shipping_method
/25931284564/checkouts/df24e48ecc81f767583c4a26680bcb82?step=shipping_method&previous_step=contact_information
/25931284564/checkouts/df24e48ecc81f767583c4a26680bcb82?_ga=2.150710640.738515769.1576779089-71346777.1571176760%26_gac%3D1.16451458.1576260301.EAIaIQobChMI9v2c5Zqz5gIVr__jBx1VAgxPEAAYBCAAEgLccPD_BwE&locale=es&step=shipping_method
/25931284564/checkouts/df24e48ecc81f767583c4a26680bcb82?_ga=2.150710640.738515769.1576779089-71346777.1571176760%26_gac%3D1.16451458.1576260301.EAIaIQobChMI9v2c5Zqz5gIVr__jBx1VAgxPEAAYBCAAEgLccPD_BwE&locale=es&step=shipping_method&previous_step=contact_information
Payment method without and with _ga
/25931284564/checkouts/df24e48ecc81f767583c4a26680bcb82?step=payment_method
/25931284564/checkouts/df24e48ecc81f767583c4a26680bcb82?step=payment_method&previous_step=shipping_method
/25931284564/checkouts/df24e48ecc81f767583c4a26680bcb82?_ga=2.150710640.738515769.1576779089-71346777.1571176760%26_gac%3D1.16451458.1576260301.EAIaIQobChMI9v2c5Zqz5gIVr__jBx1VAgxPEAAYBCAAEgLccPD_BwE&locale=es&step=payment_method
/25931284564/checkouts/df24e48ecc81f767583c4a26680bcb82?_ga=2.150710640.738515769.1576779089-71346777.1571176760%26_gac%3D1.16451458.1576260301.EAIaIQobChMI9v2c5Zqz5gIVr__jBx1VAgxPEAAYBCAAEgLccPD_BwE&locale=es&step=payment_method&previous_step=shipping_method
Any ideas how I could solve this? I am pretty sure it's simple, but my brain just doesn't get around more complex regular expressions :)
UPDATE
Just to clear this up a bit more, what I need to achieve with the regular expressions is to identify specifically the step of the funnel.
The Google Ads guys from my team are creating a funnel in Analytics and they add the corresponding steps from the checkout as stages of the funnel.
So basically I just need my regexes to be able to work with or without the _ga query, BUT always detecting a specific step.
UPDATE 2
I added all the possible matches. I need to be able to identify the specific step through the regular expression. So basically I need one regular expression for contact information, one for shipping method and one for payment method, each identifying only the specific step with or without _ga in the URL.
I believe for the checkout url you can simply use this regex:
/([0-9]+)/checkouts/([a-z0-9-]+)(?:.*step=([a-z0-9_-]+))?
no matter if the url is with/without _ga parameter.
Basically it will provide you three groups in a match, the third group will contain step parameter value, e.g.: contact_information
Example:
https://regex101.com/r/C1GuDY/1
I'm looking for a service that tells you the nearest match of a non existent domain, because it was misspelled by the user. For example, if an user writes 'hotmail.con', send a query with that and obtain as a result 'hotmail.com'.
You've picked a hard problem. A domain can be 1-63 characters long, shall contain characters [a-z0-9-], and shall not start with a hyphen. Brute forcing it not an option. If the user types in hotmail.con you could search misspellings of it, which would try homail.com and hotmale.com, which may or may not be accurate domain names, who is to know WHICH mis-spelling is the correct one? The computer would have to return a list of options to the user: "Did you mean this domain name, or maybe or that domain name?".
You might be interested in Peter Norvig's spelling corrector that Google uses to spell check queries that come in. It's one of the best spelling correctors on the planet.
http://norvig.com/spell-correct.html
Peter Norvig's Spell checker should work provided you had a body of correct domain names which is up to date. You could create your own list on the fly, by keeping a list of which sites the user has been to, and using those as the body of domain names to check against. That way, when the user selects "hotmail.con" it finds hotmail.com in your list. However, this does not protect the user from accidentally visiting: "hotmale.com". Because that is a valid site.
Here is a stackoverflow qustion about how to get all the domain names:
https://stackoverflow.com/questions/4539155/how-to-get-all-the-domain-names
The best idea is to think outside the box and do it like firefox does it. When the user starts typing hotmail.com, what they usually do is click a textbox, type "h", then "o". Have a dropdown come out with recently visited domain names that start with that.
I am trying to find the domain -- everything but the subdomain.
I have this regexp right now:
(?:[-a-zA-Z0-9]+\.)*([-a-zA-Z0-9]+(?:\.[a-zA-Z]{2,3})){1,2}
This works for things like:
domain.tld
subdomain.tld
But it runs into trouble with tld's like ".com.au" or ".co.uk":
domain.co.uk (finds co.uk, should find domain.co.uk)
subdomain.domain.co.uk (finds co.uk, should find domain.co.uk)
Any ideas?
I'm not sure this problem is "reasonably solvable"; Mozilla maintains a list of 'public suffix' domains that is intended to help browser authors accept cookies for only domains within one administrative control (e.g., prevent someone from setting a cookie valid for *.co.uk. or *.union.aero.). It obviously isn't perfect (near the end, you'll find a long list of is-a-caterer.com-style domains, so foo.is-a-caterer.com couldn't set a cookie that would be used by bar.is-a-caterer.com, but is-a-caterer.com is perfectly well a "domain" as you've defined it.)
So, if you're prepared to use the list as provided, you could write a quick little parser that would know how to apply the general rules and exceptions to determine where in the given input string your "domain" comes, and return just the portion you're interested in.
I think simpler approaches are doomed to failure: some ccTLDs such as .ca don't use second-level domains, some such as .br use dozens, and some, like lib.or.us are several levels away from the "domain" such as multnomah.lib.or.us. Unless you're using curated lists of which domains are a public suffix, you're doomed to being wrong for some non-trivial set of input strings.
I just got started looking at using Solr as my search web service. I don't know whether Solr supports these query types:
Startswith
Exact Match
Contain
Doesn't Contain
In the range
Could anyone guide me how to implement those features in Solr?
Cheers,
Samnang
Solr is capable of all those things but to adequately explain how to do each of time an answer would become a mini-manual for Solr.
I'd suggest you read the actual manual and tutorials linked from the Solr homepage.
In short though:
Startswith can be implemented using Lucene wildcards.
Exact matches will only be found if a field is not tokanized. I.e. the entire field is viewed as a single token.
Contain is the default search format. I.e. a search for "John" will find any document's whose search field contains the value "John". Prefixing with - (e.g. "-John" will only find documents that do not contain John).
Ranges (be they date or integer) are possible and quite powerful, example date:[* TO NOW] would find any document whose date is not in the future.