I'm currently learning webfocus and I'm learning about defining, but what is teaching me isn't doing a great job. An example that has been given to me is about cars. If I want to make a new field to find the difference between the retail cost and the dealer cost, they said to input
DEFINE FILE CAR
CALCULATED_DIFFERENCE/D5 = RETAIL_COST - DEALER_COST
END
What I'm confused about is what the
/D5
is there for. Is it required to define a file? Does it have to be something specific? I've researched a lot but haven't found any answers about it.
From what I understand, it joins the aliases and roots. For example the D could be short for difference. The 5 could just be a number. Without all of the example and question it's hard to say.
Here is another example http://www.hwconline.com/ibi_html/javaassist/intl/EN/help/source/topic547.htm
Section
A preceding forward slash '/' is required for all aliases and context roots. The WebFOCUS Administration Console automatically adds a forward slash if one was not entered.
I am assuming it could be a pointer. Look at the url and the / indicates like a tree node. If you want to get to a location then it's location/location/location/here
here being what your looking at. So if the /D5 is called it could mean page/page/page/Difference5 so for short it omits all of the pages and signifies the direct alias D5.
I am not entirely sure but that is what I have always thought. Look at everything dealing with locations a \ or / is always used.
I've found out what it means. The /D5 is known as formatting. It allows WebFOCUS to know what is being used in the file. The D stands for decimal, which means that if I wanted to I could format it as D/5.2 and an A stands for alphanumeric. If I were to define a file called person_last_name, I would use A/30. The number determines how much data it can hold, so 30 is all I need as a person's last name probably won't be longer than 30 characters.
Related
I'm using data from synthea and it looks like most (all?) of the given and family names I'm getting back end with a three digit number (e.g. Gregg522). Is this part of the design of synthea or am I parsing the data incorrectly. A snippet of the json I'm getting back is shown below. If this is part of the design, what is the motivation of ending the name with a number (I would think this would make the data less realistic).
Yes, they generally do. It is sometimes nice to be able to see that the patients are fake/synthetic ones. However, this is a setting you can change: In the synthea.properties file, look for the setting "append_numbers_to_person_names" and set it to false.
I have some code which has worked in multiple installations for about a year. Today im doing a small change to a control and then another control seems to have developed an issue. When at runtime im getting a 91 error object variable or with block variable not set.
I therefore looked at the problem line which is: -
If Screen.ActiveForm.name = "frmFoutmelding" Then Exit Sub
so I noticed the name was lowercase. if i delete .name and rehit the "dot" then it shows me i can use .Name but as soon as i move from this line it drops back to .name
I've checked for instances of name and it appears everywhere in the code in different modules but i cant find if i have accidentally defined this lowercase name anywhere?
Googling doesn't seem to show much but i feel Im googling the wrong terms
chaps - thanks for your suggestions - this was the first instance of the lowercase name and searching as Jim suggested didn't reveal anything I'm afraid. What I did discover was that this was suddenly being run before any forms had actually been displayed and so the count was 0. I therefore, did an on error to check the form count and exit the sub if it =0 then if not to carry on with the line I thought I was having issues with.
It's likely that you did create a new variable or property called (lower case) name, or that some included reference did the same. It's possible to use reserved words as variable names in some cases, but it requires taking specific steps.
I would first search your code for instances of name As to see if you created a variable (this assumes you use Option Explicit, which is a must IMO). Then search for Property*name with * as a wildcard.
If those fail you could try unchecking references or components to see if any of them define name. If none of that finds anything, please post back here.
Jim Mack covers a lot of the potential issues. I think another is if you typed a lower case '.name' in association with Activeform at some point earlier in the same code module - the VB6 IDE checks in the current module and uses that to define what case to use. Look further up the same code module (sub or function).
Ultimately, check what changes you made by comparing the old source to the new in a file comparison tool like windiff - you do have backups, right?
You can see on their category links that it's quite obvious that the only portion of their URL that matters is the small hash near the end of the URL itself.
For instance, Water Heaters category found under Heating/Cooling is:
http://www.lowes.com/Heating-Cooling/Water-Heaters/_/N-1z11ong/pl?Ns=p_product_avg_rating|1
and Water Heaters category found under Plumbing is:
http://www.lowes.com/Plumbing/Water-Heaters/_/N-1z11qhp/pl?Ns=p_product_avg_rating|1
That being said, obviously their structure could be a number of different things...
But the only thing I can think is it's a hex string that gets decoded into a number and denominator but I can't figure it out...
apparently it's important to them to obfuscate this for some reason?
Any ideas?
UPDATE
At first I was thinking it was some sort of base16 / hex conversion of a standard number / denom or something? or the ID of a node and it's adjacency?
Does anyone have enough experience with this to assist?
They are building on top of IBM WebSphere Commerce. Nothing fancy going on here, though. The alpha-numeric identifiers N-xxxxxxx are simple node identifiers that do not capture hierarchical structure in themselves; the structure (parent nodes and direct child nodes) is coded inside the node data itself, and there are tell-tale signs to that effect (see below.) They have no need for nested intervals (sets), their user interface does not expose more than one level at a time during normal navigation.
Take Lowe's.
If you look inside the cookies (WC_xxx) as well as see where they serve some of their contents from (.../wcsstore/B2BDirectStorefrontAssetStore/...) you know they're running on WebSphere Commerce. On their listing pages, everything leading up to /_/ is there for SEO purposes. The alpha-numeric identifier is fixed-length, base-36 (although as filters are applied additional Zxxxx groups are tacked on -- but everything that follows a capital Z simply records the filtering state.)
Let's say you then wrote a little script to inventory all 3600-or-so categories Lowe's currently has on their site. You'd get something like this:
N-1z0y28t /Closet-Organization/Wood-Closet-Systems/Wood-Closet-Kits
N-1z0y28u /Closet-Organization/Wood-Closet-Systems/Wood-Closet-Towers
N-1z0y28v /Closet-Organization/Wood-Closet-Systems/Wood-Closet-Shelves
N-1z0y28w /Closet-Organization/Wood-Closet-Systems/Wood-Closet-Hardware
N-1z0y28x /Closet-Organization/Wood-Closet-Systems/Wood-Closet-Accessories
N-1z0y28y /Closet-Organization/Wood-Closet-Systems/Wood-Closet-Pedestal-Bases
N-1z0y28z /Cleaning-Organization/Closet-Organization/Wood-Closet-Systems
N-1z0y294 /Lighting-Ceiling-Fans/Chandeliers-Pendant-Lighting/Mix-Match-Mini-Pendant-Shades
N-1z0y295 /Lighting-Ceiling-Fans/Chandeliers-Pendant-Lighting/Mix-Match-Mini-Pendant-Light-Fixtures
N-1z0y296 /Lighting-Ceiling-Fans/Chandeliers-Pendant-Lighting/Chandeliers
...
N-1z13dp5 /Plumbing/Plumbing-Supply-Repair
N-1z13dr7 /Plumbing
N-1z13dsg /Lawn-Care-Landscaping/Drainage
N-1z13dw5 /Lawn-Care-Landscaping
N-1z13e72 /Tools
N-1z13e9g /Cleaning-Organization/Hooks-Racks
N-1z13eab /Cleaning-Organization/Shelves-Shelving/Laminate-Closet-Shelves-Organizers
N-1z13eag /Cleaning-Organization/Shelves-Shelving/Shelves
N-1z13eak /Cleaning-Organization/Shelves-Shelving/Shelving-Hardware
N-1z13eam /Cleaning-Organization/Shelves-Shelving/Wall-Mounted-Shelving
N-1z13eao /Cleaning-Organization/Shelves-Shelving
N-1z13eb3 /Cleaning-Organization/Baskets-Storage-Containers
N-1z13eb4 /Cleaning-Organization
N-1z13eb9 /Outdoor-Living-Recreation/Bird-Care
N-1z13ehd /Outdoor-Living
N-1z13ehn /Appliances/Air-Purifiers-Accessories/Air-Purifiers
N-1z13eho /Appliances/Air-Purifiers-Accessories/Air-Purifier-Filters
N-1z13ehp /Appliances/Air-Purifiers-Accessories
N-1z13ejb /Appliances/Humidifiers-Dehumidifiers/Humidifier-Filters
N-1z13ejc /Appliances/Humidifiers-Dehumidifiers/Dehumidifiers
N-1z13ejd /Appliances/Humidifiers-Dehumidifiers/Humidifiers
N-1z13eje /Appliances/Humidifiers-Dehumidifiers
N-1z13elr /Appliances
N-1z13eny /Windows-Doors
Notice how entries are for the most part sequential (it's a sequential identifier, not a hash), mostly though not always grouped together (the identifier reflects chronology not structure, it captures insertion sequence, which happened in single or multiple batches, sometimes years and thousands of identifiers apart, at the other end of the database), and notice how "parent" nodes always come after their children, sometimes after holes. These are all tell-tale signs that, as categories are added and/or removed, new versions of their corresponding parent nodes are rewritten and the old, superseded or removed versions are ultimately deleted.
If you think there's more you need to know you may want to further inquire with WebSphere Commerce experts as to what exactly Lowe's might be using specifically for its N-xxxxxxx catalogue (though I suspect that whatever it is is 90%+ custom.) FWIW I believe Home Depot (who also appear to be using WebSphere) upgraded to version 7 earlier this year.
UPDATE Joshua mentioned Endeca, and it is indeed Endeca (those N-xxxxxxx identifiers) that is being used behind Websphere in this case (though I believe since the acquisition of Endeca Oracle is pushing SUN^H^H^Htheir own Java EE "Endeca Server" platform.) So not really a 90% custom job despite the appearances (the presentation and their javascripts are heavily customized, but that's the tip of the iceberg.) You should be able to use Solr as a substitute.
I'm trying to make an algorithm that easily simplifies and groups synonyms (with mismatches, capitals, acronims, etc) into only one. I supose there should exist a standard way to build such a structure that, looking for a string with possible mismatches, if the string exists in the structure, it returns a normalized string key. In short, sometimes the same concept could be written in several ways, but I only want to keep the concept.
For instance: Supose I want to normalize or simplify the appearances of
"General Director", "General Manager", "G, Dtor", "Gen Dir", ...
into
"GEN_DIR"
and keep only this result for further reference.
By the way, I suppose that building a Hash with key/value pairs like
hash["General Director"]="GEN_DIR"
hash["General Manager"]="GEN_DIR"
hash["G, Dtor"]="GEN_DIR"
hash["G, Dir"]="GEN_DIR"
could be a solution, but I suspect that there are more elegant or adequate solutions to that.
I would also need the way to persist this associative structure easily without any database because it should grow as I find more mismatches of the same word or sentence. A possible approach I think is to define this structure by means of a DSL, but I'm open to suggestions.
Well, there is no rule, at least a clear one.
My aim is to scrap from web some "structured" data that sometimes is incorrectly or incompletely typed. Some fields are descriptions and can be left as is. But some fields are suposedly to be "sets" but aren's correctly typed (as in my example). As a human can read that, he immediatelly knows what it means and can associate that with its meaning.
But I would like to automate as much as possible the process of reducing those possible mismatches to only one "string" (or symbol) before, for instance, saving it into a database. So, what I would need is a kindof hash or dictionary, as sawa correctly stated, that I can use to lookup any of such dirty strings to get the normalized string or symbol.
Also, of course, it would be desirable a way to make this hash (or whatelse it could be) to learn from new mismatches in some way and add a new association automatically (possibly it could be based on a distance measure between mismatched string and normalized string that, if lower than X, a new association is built). The whole association (i.e, hash) should grow as new mismatches and concepts arise and, though, it should be kept anywhere (possibly in an xml file, or something like what Mori answered below) for future uses.
Any new Idea?
To make matter more specific:
How to detect people names (seems like simple case of named entity extraction?)
How to detect addresses: my best guess - find postcode (regexes); country and town names and take some text around them.
As for phones, emails - they could be probably caught by various regexes + preprocessing
Don't care about education/working experience at this point
Reasoning:
In order to build a fulltext index on resumes all vulnerable information should be stripped out from them.
P.S. any 3rd party APIs/services won't do as a solution.
The problem you're interested in is information extraction from semi structured sources. http://en.wikipedia.org/wiki/Information_extraction
I think you should download a couple of research papers in this area to get a sense of what can be done and what can't.
I feel it can't be done by a machine.
Every other resume will have a different format and layout.
The best you can do is to design an internal format and manually copy every resume content in there. Or ask candidates to fill out your form (not many will bother).
I think that the problem should be broken up into two search domains:
Finding information relating to proper names
Finding information that is formulaic
Firstly the information relating to proper names could probably be best found by searching for items that are either grammatically important or significant. I.e. English capitalizes only the first word of the sentence and proper nouns. For the gramatical rules you could look for all of the words that have the first letter of the word capitalized and check it against a database that contains the word and the type [i.e. Bob - Name, Elon - Place, England - Place].
Secondly: Information that is formulaic. This is more about the email addresses, phone numbers, and physical addresses. All of these have a specific formats that don't change. Use a regex and use an algorithm to detect the quality of the matches.
Watch out:
The grammatical rules change based on language. German capitalizes EVERY noun. It might be best to detect the language of the document prior to applying your rules. Also, another issue with this [and my resume sometimes] is how it is designed. If the resume was designed with something other than a text editor [designer tools] the text may not line up, or be in a bitmap format.
TL;DR Version: NLP techniques can help you a lot.