I'm currently creating a survey on Google Form and I need to make it in 4 languages so the result of each questions are not separated depending on the language selected by the user. (so we can have graphical results of each responses without taking language into account)
This raises different questions:
1- Should I create different forms from the beginning (one for each language) OR is it better to merge all languages surveys into one & only google form linking questions by possible script/else?
2- What would be the best script to allow adding questions to the survey in the future while keeping the most accurate graph results?
3- Is it possible to give only one link to people so they decide in which language they want to take the survey? (maybe creating one form for the only purpose of choosing language, then re-direct to appropriate form?)
I really checked & couldn't find which way to create a multi-langual survey on Google Form... (if needed I will separate each questions but they are pretty linked to each other...)
You can do it this way.
First, add a radio button question to allow the user to select their preferred language.
Then, create four sections in the form, each for one language.
Next, click on the three dots and select "Go to section based on answer". Make different options "redirect" to different language sections.
Related
I am new at the idea of programming algorithms. I can work with simplistic ideas, but my current project requires that I create something a bit more complicated.
I'm trying to create a categorization system based on keywords and subsets of 'general' categories that filter down into more detailed categories that requires as little work as possible from the user.
I.E.
Sports >> Baseball >> Pitching >> Nolan Ryan
So, if a user decides they want to talk about "Baseball" and they filter the search, I would like to also include 'Sports"
User enters: "baseball"
User is then taken to Sports >> Baseball
Now I understand that this would be impossible without a living - breathing dynamic program that connects those two categories in some way. It would also require 'some' user input initially, and many more inputs throughout the lifetime of the software in order to maintain it and keep it up to date.
But Alas, asking for such an algorithm would be frivolous without detailing very concrete specifics about what I'm trying to do. And i'm not trying to ask for a hand out.
Instead, I am curious if people are aware of similar systems that have already been implemented and if there is documentation out there describing how it has been done. Or even some real life examples of your own projects.
In short, I have a 'plan' but it requires more user input than I really want. I feel getting more info on the subject would be the best course of action before jumping head first into developing this program.
Thanks
IMHO It isn't as hard as you think. What you want is called Tagging and you can do it Automatically just by setting the correlation between tags (i.e. a Tag can have its meaningful information plus its reation with other ones. Then, if user select a Tag well, you related that with others via looking your ADT collection (can be as simple as an array).
Tag:
Sport
Related Tags
Football
Soccer
...
I'm hoping this helps!
It sounds like what you want to do is create a tree/menu structure, and then be able to rapidly retrieve the "breadcrumb" for any given key in the tree.
Here's what I would think:
Create the tree with all the branches. It's okay if you want branches to share keys - as long as you can give the user a "choice" of "Multiple found, please choose which one... ?"
For every key in the tree, generate the breadcrumb. This is time-consuming, and if the tree is very large and updating regularly then it may be something better done offline, in the cloud, or via hadoop, etc.
Store the key and the breadcrumb in a key/value store such as redis, or in memory/cached as desired. You'll want every value to have an array if you want to share keys across categories/branches.
When the user selects a key - the key is looked up in the store, and if the resulting value contains only one match, then you simply construct the breadcrumb to take the user where you want them to go. If it has multiple, you give them a choice.
I would even say, if you need something more organic, say a user can create "new topic" dynamically from anywhere else, then you might want to not use a tree at all after the initial import - instead just update your key/value store in real-time.
I got a financial application and I wish to add to it the ability to get user command or input in textbox and then take the right action. for example, wish the user to write "show the revenue in the last 10 days" and it'll show the revenue to him/her - the point is that I wish it to really understand the meaning of the question, so the previus statement will bring the same results as "do I got any revenue in the last 10 days" or something like that - BI (something like the Wolfram|Alpha engine).
I wonder if there's any opensource library or algorithm books or whatever that I can use to learn the subject. Regards to opensource libraries - I don't mind which language it'll be written in.
I've read about this subject and saw many engines and services (OpenNLP, Apache UIMA, CoreNLP etc.) but did not figure out if they're right for my needs.
Any answer or suggestion is welcome.
Many thanks!
The field you're talking about is usually called "natural language processing". It's hard, and an active field of research. There are various libraries which you could consider based on your preferred programming language and use case:
http://en.wikipedia.org/wiki/List_of_natural_language_processing_toolkits
I've used NLTK a little bit. This field is seriously difficult to get right, so you might want to try to restrict your application to some small set of verbs and nouns such that people are using a controlled vocabulary in the first instance, and then try to extend it beyond that.
We are using DevExpress XtraReports 2009v3.3 and although I can achieve what I want through various formatting objects in code, there must be a (better/less painless/maintainable/visual) way of achieving what I require...
I need to produce a report, designed to end-user 'look & feel'. We have many companies which use our software and they all require different design schema's/templates for their reports. For example - a single report, depending on who logs on (we know what company they belong to) apply the template the report should use.
As an example, some of the requirements (per end-user/company) include:
their own logo (positioned in the correct place),
Margins being of specific size
their own fonts (or font choice)
alternating colours schemes
Specific rows / columns being particular colours (both permanently and based on value)
Formatting of values, for example a european user would get euro, a uk user gets pounds on certain columns/cells/rows.
I know there is an End-User Report Designer, however this isn't what we require - I must create the schema/template design for a report then apply it at runtime.
Also using save/load layout for multiple repx files isn't the best solution as a change to the report would cause a lot of extra work as you would have to update each repx template file.
It is possible to create different reports and save it to the repx format via XtraReport.SaveLayout method and use these repx files as template.
Similar but different question
I asked dev express and they basically said there isn't any 'layout abstraction' that would do what I require.
I've read somewhere (can't remember/find where) an article about web usability describing when to use drop downs and when to use autocomplete fields.
Basically, the article says that the human brain cannot store more then the last five options presented to choose.
For example, in a profile form, where there is your current occupation, and the system gives you a bunch of options, when you read the sixth options, your brain can't remember the first one anymore. This example is a great place to use an autocomplete field, where the user types something that he thinks that would be his occupation and then select the better from the few options filtered.
I would like to hear your opinion about this subject.
When should I use a drop-down and when I should use a Autocomplete field?
For a limited list, don't use an autocomplete edit box or combobox, but use a listbox where all values are visible all at once. For limited lists, especially with static content of up to about 8 items, this takes up real estate, but presents the user with a better immediate overview.
For less than 5 items a radiogroup or checkbox group (multiple selections) may also be better.
For lists whose content is dynamic, like a list of contacts, a (scrolling) listbox or combobox are appropriate because you never know how many items will be in the list. To keep it manageable, you will need to allow for some kind of filtering and/or autocomplete.
Autocomplete usually suffers from the fact that what the users types needs to match a string from the beginning. I hate those except for when they are used to complete a value based on what I typed in that (type of) field before. E.g. what browsers nowadays offer when filling out online forms.
Allowing a user to start typing in a combobox usually suffers the same drawback. But admittedly it doesn't need to if the filtering is based on "like %abc%" instead of "starts with abc"
When dealing with lists that can have many similar items, I really like the way GMail's "To" field handles it. You start typing any part of someone's name or e-mail address and GMail will drop down a list presenting all the contacts whose name or e-mail address contains the characters you have typed so far anywhere within them. Using the up and down keys changes the selection in the dropped down list (without affecting what you have typed) and pressing enter adds the currently selected item to the "To" field. By far the best user experience I have had so far when having to select something from a list.
Haven't found any components yet that can do this, but it's not too hard to "fake" by combining an edit box and a listbox that drops down when you start typing and has its contents is filtered based on what has been typed so far.
I would use 2 criteria,
1) How long is the list, if the list contains 5 elements you better use a combobox as it will be easier for the user (better UX)
2) In case the list is long, how easy for the user to remember the prefix of what he/she is looking for... if it's not easy, using autocomplete is irrelevant..
I'd say it depends on the diversity in the list, and the familiarity with the list items.
If for example the list contained over 5 car brands (list items I'm familiar with), no problem.
If on the other hand the list has over 5 last names, it could take me some more time before I'd make a selection.
You should probably just try out both options and trust your gut on which you find easier to use.
Here's the opposite approach:
The worst time to use an auto-complete box is when you have a finite and relatively small set of options, and the user doesn't know the range of valid options. For example, if you're selling used cars and you have a mixed bag of brands, simply listing the brands in a combobox is more efficient and easier to browse than an auto-complete method.
Being able to remember the last 5 options is most likely irrelevant unless you have a giant list of options and are requiring the user to select the most relevant item.
An alternative approach is to use both. I believe Dojo has a widget that acts as both a combobox and an auto-complete field. You can either choose to start typing and it will narrow down the possible options, or you can interact with it with your mouse and browse it like a combobox.
I usually look at how big the list is going to be. If there are going to be more than 15 options then it just seems easier to find if they can just start typing.
The other circumstance for me is when there is an other option and they can free type it. This essentially eliminates the need for two controls since you can combine in one.
The main difference has nothing to do with usability but more to do with what defines the acceptable inputs.
You normally use a ComboBox when you have a predefined list of acceptable inputs (e.g. an Enum or list of occupations).
An auto-complete field is best used when there are many known inputs BUT custom input is accepted as well. The user will become frustrated if they type "Programmer" in as their occupation but it wasn't one of the pre-defined, acceptable inputs, and they are given a message that their input is not valid.
Keep in mind that ComboBoxes do allow you to type in them to select the first matching option. Some types of ComboBoxes (depending on the UI framework you are using) even allow free-form text fields at the top or side of the field to search or add to the list.
Of coarse the best way to determine what YOUR user will prefer is testing: A/B, field, user, etc.
Hope this helps you solve your dilemma!
I am wondering what algorithm would be clever to use for a tag driven e-commerce enviroment:
Each item has several tags. IE:
Item name: "Metallica - Black Album CD", Tags: "metallica", "black-album", "rock", "music"
Each user has several tags and friends(other users) bound to
them. IE:
Username: "testguy", Interests: "python", "rock", "metal", "computer-science"
Friends: "testguy2", "testguy3"
I need to generate recommendations to such users by checking their interest tags and generating recommendations in a sophisticated way.
Ideas:
A Hybrid recommendation algorithm can be used as each user has friends.(mixture of collaborative + context based recommendations).
Maybe using user tags, similar users (peers) can be found to generate recommendations.
Maybe directly matching tags between users and items via tags.
Any suggestion is welcome. Any python based library is also welcome as I will be doing this experimental engine on python language.
1) Weight your tags.
Tags fall into several groups of interest:
My tags that none of my friends share
Tags a number of my friends share, but I don't
My tags that are shared by a number of my friends.
(sometimes you may want to consider friend-of-a-friend tags too, but in my experience the effort hasn't been worth it. YMMV.)
Identify all tags that the person and/or the person's friends have in interests, and attach a weight to the tags for this individual. One simple possible formula for tag weight is
(tag_is_in_my_list) * 2 + (friends_with_tag)/(number_of_friends)
Note the magic number 2, which makes your own opinion worth twice as much as that of all of your friends put together. Feel free to tweak :-)
2) Weight your items
For each item that has any of the tags in your list, just add up all of the weighted values of the tags. A higher value = more interest.
3) Apply a threshold.
The simplest way is to show the user the top n results.
More sophisticated systems also apply anti-tags (i.e. topics of non-interest) and do many other things, but I have found this simple formula effective and quick.
If you can, track down a copy of O'Reilly's Programming Collective Intelligence, by Toby Segaran. There's a model solution in it for exactly this problem (with a whole bunch of really, really good other stuff).
Your problem is similar to product recommendation engines, such as Amazon's well publicized site. These use a learning algorithm called association rules, which basically build a conditional probability of user X buying product Y based on common features Z between the user and product. A lot of open source toolkits implement association rules, such as Orange and Weka.
You can use the Python Semantic module for Drools to specify your rules in python scripting language. You can accomplish this easily using Drools. It is a terrific rules engine that we used to solve several recommendation engines.
I would use a Restricted Boltzmann Machine. Gets around the problem of similar but not identical tags quite neatly.