In WCS7, is there any limitation to the bumber of itembeans associated to a Product bean
There is no hard limit in how many items (SKUs) you can have for each product, but you should consider the performance implications, both for listing on the product page, but also the size of your attribute tables.
I would challenge that if you have this need, there may be better approaches, e.g. if you're trying to model an ability to customize a product (e.g. "I want 20cm of this fabric"), you can use the product attribute model (see the PATTRIBUTE table) to allow shoppers to add custom attributes to the product when they add to cart.
The Extending an SOI service with UserData tutorial in the V7 Knowledge Center shows an example of doing so through engraving attributes for a product.
Yes, This is possible. considering the performance issues that can happen in PDP, if the product have to diaply all the variation details in PDP.
Related
How to I create an #Intent which looks something like this:
How much is a #ProductType?
Whereas the #ProductType is an simple Entity which consists of:
Soft Drinks: Coke, Pepsi, Sprite, Fanta
Fruits: Apple, Banana, Watermelon
I tried adding an Intent with above settings, but it doesn't seem to work. Is such ability natively supported in IBM Watson? Or otherwise, do I need to manually handle in the Dialog, using Conditions and stuffs? Please kindly advise.
The training is based on regular language and typical sentences or phrases. So #ProductType is not what you want in the phrase, but any of the fruits or drinks.
By defining the entities, Watson Assistant later learns the connection and to identify the entities and intents.
To get started, you define the intents and entities. Both can be imported from lists. Then you add the dialog which references the different types.
This blog should give insight to all the ways to train an entity and how it is used within intents.
https://medium.com/ibm-watson/all-about-entities-dictionaries-and-patterns-with-watson-assistant-part-1-5ef7254df76b
There are a number of possible pipelines you can choose from.
1. Indirect references: this is the preferred method.
Use natural language in your intent training data. "I want to buy a pear"
Watson will automatically see the other values you have related to pear and use those as intent training as well. This will be the fastest and simplest way to manage your data
2. Direct references: this should only be used if absolutely necessary
Directly reference the entity in your intent data. "I want to buy an #pear"
Nothing is done in the UI to tell you this works, but it does. This tells Watson the entity is a very important term and will increase the weight, as well as reference all synonyms with high weight. This is more effort for you to go through your entire workspace and relabel everything this way, hence why it is not recommended unless absolutely necessary. By doing this, you also tell watson that when the system sees various fruits without the # symbol, to ignore them as entities which is not ideal
3. Contextual entities. This is highlighting them like in your screenshot.
Note the UI has been updated so there is no an annotation mode instead of just highlighting. This builds a model around the entity, and is good for things like names or locations, but not necessary for a small list of items like crayons in a box, or fruit in a store. This will ignore all of the dictionary values youve created and only look at the model. It should be used according to the blog above when the use case is ideal.
What #data_henrik answered was partially correct. But it doesn't seem like Watson Assistant "automatically" learns the preferred #Entity just by simply inputting the pure (plain-text) Examples into the #Intent. In fact, that step was required. But we still need to do one more step.
After keying in the good plain-text Examples into the #Intent, we then still need to "right click" on the text-string of the possible #Entity entry, and then choose (teach Watson) the correct #Entity name from the dropdown list appeared.
Only then Watson starts to understand such; this #Intent uses that #Entity, I suppose.
Thank you #data_henrik, and appreciate your hint.
I am creating a database in MS-Access to manage product specifications. Some products have overlapping specifications and some are unique.
My initial approach to this problem was to create multiple forms. For Example: an extension cord specification needs copper, compound and plug information. This information is also needed for a power strip specification, as well as other information that is ONLY pertinent to power strips. Currently I have created multiple forms for the different products. Is it possible to save multiple forms into a pdf for the same part number?
I know I can create a long form that is split on different pages, this method could work if I could not save or print certain pages depending on the product too. Any help is greatly appreciated.
I have shown in the picture below a portion of the forms and how some information is relevant only to the product class.
I know I could create forms for a basis of every category of inventory, but then I would have to create a full specification form for over 10 products, I am trying to streamline and reduce the amount of front end work required to generate specs from our database
So i'm setting up my ld+json structured data, using Schema.org schemas. I am adding products with Offers but they only have a single price parameter.
I also looked at PriceSpecification too, but there is only "range" and "price".
Should I use 2 PriceSpecifications (or 2 Offers?) with visibly different names, or is there another option I haven't come across? Don't want search engines to get confused.
Thanks for any help.
You can use multiple PriceSpecifications. However "typically, only the subclasses of this type are used for markup." UnitPriceSpecification would be the best fit, or the setup price can be of type DeliveryChargeSpecification.
Alternatively, you can use a single CompoundPriceSpecification with multiple priceComponent properties, each of type UnitPriceSpecification. "The name property of the attached unit price specification for indicating the dimension of a price component"
Suppose I have a store such as Amazon that sells a variety of products such as computers and paintings. They are quite different from each other and have their own set of fields and logic.
In addition to the typical CRUD, I need to design a JSON API that allows me to:
A. Fetch an ungrouped list of paintings and computers. For example: [computer, painting, painting, computer, ...] ordered by date published (so with filtering capability).
B. Fetch only paintings
C. Fetch only computers
The RESTful approach will typically be something like: /api/paintings and api/computers which works really well for segregated results.
But my main concern is operation A - getting an ungrouped list of paintings and products sorted by date published. The way I see it, there are three approaches:
1) Create a new standalone resource called products such as /api/products which will have filtering capability and continue to use /api/resource for specific CRUD operations.
2) Create a parent products resource which will be used for filtering operations. So I can do something like /products?order_by=published_date And for more specific resources I can do something like /products/paintings or /products/computers
3) Do not have a resource for paintings or computers. Instead have one for a generic product. I will then have most logic in the api layer and reduce the complexity of the client.
I am leaning towards approach #3 but wanted to get feedback prior to implementing since this will be a core feature of the API.
I've always taken the approach the your API Layer should match your object modeling. So, the answer to your question would be it depends on the source data. Well, the source data after it's object modeling.
If you have an object model for Computer and for Printer, they should be resources like you've said. Do they share any data/functions? If so, you should have an object model for that, too, perhaps: Product. Then Computer and Printer extend the Product class.
With that in mind, design the API layer to mirror it. Since Computer and Printer both extend Product. Product as a parent of the Computer and Printer resources make sense.
In my opinion I would go for approach #3 and query the API with type of product if you search for it.
/products?type=computers&order_by=date
We recently started to work in a big project and we decided to use MongoDB as a DDBB solution.
We wrote a lot of code, but the project has started to grow and we found out that we're trying to use joins instead of doing it the NoSQLway, which denotes a bad DDBB design.
What I'm trying to ask here is a good design for our project, which, at this point consists of the following:
More than 12.000 Products
More than 2.000 Sellers
Every seller should have its own private area that will allow to create a product catalog based on the +12.000 "products template list".
The seller should be able to set the price, stock and offers, which will then be reflected only in his public product listing. The template list of products will remain unchanged.
Currently we have two collections. One for the products (which holds the general product information, like name, description, photos, etc...) and one collection in which we store documents that contain the ID of the product from the first collection, an ID that is related to the seller and the stock, price and offers values.
We are using aggregate with $lookup to "emulate" SQL's left join to merge the two collections, but the process is not scaling as we'd like it to and we're hitting serious performance issues.
We're aware that using joins is not the way to go in NoSQL. What should we do? How should we refactor our DDBB design? Should we embed the prices, offers and stock for each seller in each document?
The decision of using "Embedded documents" or "Joins among two or more different collections" should depend on how you are going to retrieve the data.If every time,while fetching product, you are going to fetch sellers,then it makes sense to make it an embedded document instead of different collections.But if you will be planning to fetch these two entities separately, then only option you are left with is to use Join.