In order to pass FedEx certification for the shipment API, they requested the label to have conditions of carriage.
Here is exact response from the FedEx representative:
The labels you forwarded still did not have any Conditions of carriage on them . this is what it should look like on the second part of the label (note this is a ss of a Spanish version)
Attached example was a copy of the text from here:
http://www.fedex.com/mx/services/nacional_terms.html
I also noticed that different services might have a different terms and conditions, so, wondering how should we handle it on our side? Should it be a custom text specified through CustomerSpecifiedDetail or is there is a way we could use some defaults?
The presence of the Conditions of the Carriage on the Label depend on the LabelStockType(see FedEx xml guide) tag.
For example:
PAPPER_LATTER - will produce a labels without terms and conditions on it;
PAPER_8.5X11_TOP_HALF_LABEL - will produce the labels with terms and conditions on it.
Related
I'm trying to do a little bit of analysis on the topics of emails I receive. I have the emails in a Google-sheet in the format below. I'm trying to count how often 'privacy' or 'confidentiality' are mentioned. My challenge is that pretty much every email signature mentions one of those words, so when i use SEARCH every cell returns TRUE.
Most email signatures start with similar phrases, so I tried deleting anything after those phrases with this formula:
=ArrayFormula(TRIM(LEFT(B1:B,MIN(IFERROR(FIND({" This email and any","IMPORTANT NOTICE", " Important notice","The information in this email"," The contents of this message"," Information in this email including"," This electronic mail message"," this message and any attachments"," This message is intended for the addressee only"," This email is CONFIDENTIAL"},B1:B),LEN(L2))))))
Column B is the column with the email body text in.
However that seems to be deleting text that follows words that aren't in my search (deleting everything after 'not' instead of 'IMPORTANT NOTICE' for instance).
Could anyone advise on either:
what's wrong with my above search
an alternate way of searching for 'privacy' and 'confidentiality' without including text from email signatures.
Example table:
|email title|email body|
|-----------|----------|
|Do you want to buy my stuff| Hi there, I'd like to know if you'd like to buy this thing I want to sell you. IMPORTANT: this email is private|
|two-for-the-price-of-one| I've a great offer for you! This email and attachments are private & confidential|
|Last chance to buy stuff!| Can we have a private call about whether you want to buy my stuff yet?|
In the example above I want to count row 3, but not rows 1 & 2, as the 'private' and 'confidential' mentions in 1 & 2 are in the signature.
Thanks!
I think I understand the error that you've described is occuring with your formula. Once the formula finds one of the values you are using to try to identify an email signature, such as " Important notice", and returns the location of that text, let's say position 96, it then uses 96 for all of the cells, like this: LEFT(B1:B,96). So you might not be able to do the compound arrayformula of an arrayformula that you are trying.
Using the formula like this, in B2, and dragging it down, should work though:
=ArrayFormula(TRIM(LEFT(B2,MIN(IFERROR(
FIND({" This email and any","IMPORTANT NOTICE", " Important notice","The information in this email"," The contents of this message"," Information in this email including"," This electronic mail message"," this message and any attachments"," This message is intended for the addressee only"," This email is CONFIDENTIAL"},B2),
LEN(L2))))))
Note: I'm not sure what value is in your L2.
But for the overall approach, it really depends on how well your terms to identify email signatures work, so as to exclude them from your final full text searches.
I would like to add a custom field to the shipping label generated by Shippo to identify the physical package. Is there any way to add custom text to the shipment label using the API?
I'm specifically looking at the Shipment, Transaction Create API call.
Yes, there is a way to add custom fields to shipping labels. There are two parameters that can be passed to create transaction, when creating a Shipment which will be printed on the label.
reference_1
reference_2
Shippo allows the max length of the field at 50 characters, but some carriers may truncate at around 30. So print a test label.
I want to do a phrase match search like "warrenton home values" but I'd like to make sure home+values stay in that order but can be switched so that "home values warrenton" and "warrenton home values" will both trigger.
I thought the + sign would "chain" the two words, home+values together but after a chat with a Google rep I find myself more confused than before. What is the best way to achieve this?
Will this phrase also trigger warrenton island home values keyword search or does the use of quotes only match words found within the quotes? I need to make sure I keep warrenton in the search phrase to avoid wasting budget on triggering ads outside of the geographic area.
You can add a modifier, the plus sign on your keyboard (+), to any of the terms that are part of your broad match keyword phrase. By adding a modifier, your ads can only show when someone's search contains those modified terms, or close variations of the modified terms, in any order. The modifier won't work with phrase match or exact match keywords.
Example: +women's +hats
Example Search: hats for women
Unlike broad match keywords, modified broad match keywords won't show your ad for synonyms or related searches. For this reason, it adds an additional level of control. Using broad match modifier is a good choice if you want to increase relevancy even if it means you might get less ad traffic than broad match.
More information here: https://support.google.com/adwords/answer/2497836?hl=en&authuser=1
I have already asked a similar question earlier but I have notcied that I have big constrain: I am working on small text sets suchs as user Tweets to generate tags(keywords).
And it seems like the accepted suggestion ( point-wise mutual information algorithm) is meant to work on bigger documents.
With this constrain(working on small set of texts), how can I generate tags ?
Regards
Two Stage Approach for Multiword Tags
You could pool all the tweets into a single larger document and then extract the n most interesting collocations from the whole collection of tweets. You could then go back and tag each tweet with the collocations that occur in it. Using this approach, n would be the total number of multiword tags that would be generated for the whole dataset.
For the first stage, you could use the NLTK code posted here. The second stage could be accomplished with just a simple for loop over all the tweets. However, if speed is a concern, you could use pylucene to quickly find the tweets that contain each collocation.
Tweet Level PMI for Single Word Tags
As also suggested here, For single word tags, you could calculate the point-wise mutual information of each individual word and the tweet itself, i.e.
PMI(term, tweet) = log [ P(term, tweet) / (P(term)*P(tweet))
Again, this will roughly tell you how much less (or more) surprised you are to come across the term in the specific document as appose to coming across it in the larger collection. You could then tag the tweet with a few terms that have the highest PMI with the tweet.
General Changes for Tweets
Some changes you might want to make when tagging with tweets include:
Only use a word or collocation as a tag for a tweet, if it occurs within a certain number or percentage of other tweets. Otherwise, PMI will tend to tag tweets with odd terms that occur in just one tweet but that are not seen anywhere else, e.g. misspellings and keyboard noise like ##$##$%!.
Scale the number of tags used with the length of each tweet. You might be able to extract 2 or 3 interesting tags for longer tweets. But, for a shorter 2 word tweet, you probably don't want to use every single word and collocation to tag it. It's probably worth experimenting with different cut-offs for how many tags you want to extract given the tweet length.
I have used a method earlier, for small text content such as SMSes, where I would just repeat the same line two times. Surprisingly, that works well for such content where a noun could well be the topic. I mean, you don't need it to repeat for it to be the topic.
I'm looking for advice on parsing input from a user in multiple combinations of City / State / Zip Code / Country.
A common example would be what Google maps does.
Some examples of input would be:
"City, State, Country"
"City, Country"
"City, Zip Code, Country"
"City, State, Zip Code"
"Zip Code"
What would be an efficient and correct way to parse this input from a user?
If you are aware of any example implementations please share :)
The first step would be to break up the text into individual tokens using spaces or commas as the delimiting characters. For scalability, you can then hand each token to a thread or server (if using a Map-Reducer like architecture) to figure out what each token is. For instance,
If we have numbers in the pattern, then it's probably a zip code.
Is the item in the list of known states?
Countries are also fairly easy to handle like states, there's a limited number.
What order are the tokens in compared to the common ways of writing an address? Most input will probably follow the local post office custom for address formats.
Once you have the individual token results, you can glue the parts back together to get a full address. In the cases where there are questions, you can prompt the user what they really meant (like Google maps) and add that information to a learned list.
The easiest method to add that support to an applications, assuming you're not trying to build a map system, is to query Google or Yahoo and ask them to parse the date for you.
I am myself very fascinated with how Google handles that. I do not remember seeing anything similar anywhere else.
I believe, you try to separate an input string in words trying various delimeters - space, comma, semicolon etc. Then you have several combinations. For each combination, you take each words and match it against country, city, town, postal code database. Then you define some metric on how to evaluate the group match result for each combination. Here should also be cross rules, like if the postal code does not match well, but country, city, town match well and in combination refer to a valid address then the metric yields a high mark.
It is sure difficult and not an evening code exercise. It also requires strong computational resources - a shared hosting would probably crack under just 10 requests, but a data center could serve it well.
Not sure if there is an example implementation. Many geographical services are offered on paid basis. Something that sophisticated as GoogleMaps would likely cost a fortune.
Correct me if I'm wrong.
I found a simple PHP implementation
http://www.eotz.com/2008/07/parsing-location-string-php/
Yahoo seems to have a webservice that offers the functionality (sort of)
http://developer.yahoo.com/geo/placemaker/
Openstreetmap seems to offer the same search functionality on its homepage
http://www.openstreetmap.org/
Assuming you're only dealing with those four fields (City Zip State Country), there are finite values for all fields except for City, and even that I guess if you have a big city list is also finite. So just split each field by comma then check against each field list.
Assuming we're talking US addresses-
Zip is most obvious, so check for
that first.
State has 50x2 options
(California or CA), check that next
Country has ~190x2 options, depending
on how encompassing you want to be
(US, United States, USA).
Whatever is left over is probably your City.
As far as efficiency goes, it might make sense to check a handful of 'standard' formats first, like Dan suggests.