I have sample sentences like
What is 1 third of 9
what is 2/5 of twenty
I can catch the number easily in the end. But there doesn't seem to be a system entity for fractions. Should I make my own? And am I right that I would need to write out every variation of every fraction I want to support?
there is no system entity for this. No.
But you can try your luck with composite entities.
With them you could create an entity which represents something like this:
"#sys.number divided by #sys.number" for "two divided by five"
"#sys.number #sys.ordinal" for "two fifths"
I am not sure if Dialogflow understands "half" or "quarter", so maybe you have to add them as well. But then you can then use them in a composite entity like above. Maybe you have to add "a" = 1 as well.
"What is the half of twenty." => 1/2 * 20
"What is a fifth of twenty." => 1/5 * 20
"What is two quarters of twenty." => 2/4 * 20
Related
I am new to Genetic Algorithm and Here is a simple part of what i am working on
There are factories (1,2,3) and they can server any of the following customers(ABC) and the transportation costs are given in the table below. There are some fixed cost for A,B,C (2,4,1)
A B C
1 5 2 3
2 2 4 6
3 8 5 5
How to solve the transportation problem to minimize the cost using a genetic algorithm
First of all, you should understand what is a genetic algorithm and why we call it like that. Because we act like a single cell organism and making cross overs and mutations to reach a better state.
So, you need to implement your chromosome first. In your situation, let's take a side, customers or factories. Let's take customers. Your solution will look like
1 -> A
2 -> B
3 -> C
So, your example chromosome is "ABC". Then create another chromosome ("BCA" for example)
Now you need a fitting function which you wish to minimize/maximize.
This function will calculate your chromosomes' breeding chance. In your situation, that'll be the total cost.
Write a function that calculates the cost for given factory and given customer.
Now, what you're going to do is,
Pick 2 chromosomes weighted randomly. (Weights are calculated by fitting function)
Pick an index from 2 chromosomes and create new chromosomes via using their switched parts.
If new chromosomes have invalid parts (Such as "ABA" in your situation), make a fixing move (Make one of "A"s, "C" for example). We call it a "mutation".
Add your new chromosome to the chromosome set if it wasn't there before.
Go to first process again.
You'll do this for some iterations. You may have thousands of chromosomes. When you think "it's enough", stop the process and sort the chromosome set ascending/descending. First chromosome will be your result.
I'm aware that makes the process time/chromosome dependent. I'm aware you may or may not find an optimum (fittest according to biology) chromosome if you do not run it enough. But that's called genetic algorithm. Even your first run and second run may or may not produce the same results and that's fine.
Just for your situation, possible chromosome set is very small, so I guarantee that you will find an optimum in a second or two. Because the entire chromosome set is ["ABC", "BCA", "CAB", "BAC", "CBA", "ACB"] for you.
In summary, you need 3 informations for applying a genetic algorithm:
How should my chromosome be? (And initial chromosome set)
What is my fitting function?
How to make cross-overs in my chromosomes?
There are some other things to care about this problem:
Without mutation, genetical algorithm can stuck to a local optimum. It still can be used for optimization problems with constraints.
Even if a chromosome exists with a very low chance to be picked for cross-over, you shouldn't sort and truncate the chromosome set till the end of iterations. Otherwise, you may stuck at a local extremum or worse, you may get an ordinary solution candidate instead of global optimum.
To fasten your process, pick non-similar initial chromosomes. Without enough mutation rate, finding global optimum could be a real pain.
As mentioned in nejdetckenobi's answer, in this case the solution search space is too small, i.e. only 8 feasible solutions ["ABC", "BCA", "CAB", "BAC", "CBA", "ACB"]. I assume this is only a simplified version of your problem, and your problem actually contains more factories and customers (but the numbers of factories and customers are equal). In this case, you can just make use of special mutation and crossover to avoid infeasible solution with repeating customers, e.g. ["ABA", 'CCB', etc.].
For mutation, I suggest to use a swap mutation, i.e. randomly pick two customers, swap their corresponding factory (position):
ABC mutate to ACB
ABC mutate to CBA
In Australia it is totally normal for a voice-assistant user to speak digit strings with 'double' and 'triple'. (Same in the UK - Where they also sometimes use "treble")
So "8845" is said "double eight four five".
"6663" will often be said as "triple six three".
Dialogflow doesn't seem to support this for any of the system digit-string entities that aim to understand a user speaking a string of digits.
So, anyone know how to support "double" and "triple" in digit strings in Dialogflow?
Do I have to 'roll my own'?
To handle these cases, you can create a dev mapping entity (let's call it "number-extra"):
reference value synonyms
88 double eight
666 triple six
Since there are only 10 "double" or "triple" variants (one for each digit), you can just create a mapping for each one (11, 22, 33, etc).
You also need a composite entity (let's call it "number"):
#numbers-extra
#sys.number
Both entities should return strings, so there will be no inconsistencies in the composite entity and the reference values should be easy to handle on the backend.
You should also add training phrases that use these entities, e.g. "My address is triple six three Main Street" and annotate the entities accordingly. This gives your model more information about how these entities are used and will improve accuracy.
This suggestion can be generalized for other sys entities as well. Missing city? Create an entity for cities and combine it with #sys.geo-city in a composite entity. Missing given-name? Same procedure.
You can use SSML and some logic to accomplish this.
Parse "468826661" to be four six double eight two triple six one and then just send it like that in a <speak></speak> tag.
Here are the docs for that.
I am in doubt about result of the following :
Each person can choose whether to wear a black tux or a grey tux, and whether to wear blue, yellow, or green coloured tie. In how many ways will you distribute all possible sets to 6 different people and no set repeats given that person 1 wants only a black tux.
A possible explanation will be helpful.
First of all, I don't think this question belongs on this stackexchange website. However what the hell I'll answer anyway.
So there are 6 people that can choose from 2 sets, the tux (2 options) and the tie (3 options)
Let's simplify a bit, one person can choose from 6 (3 * 2) options. A person with a fixed tux choice will only have 3 (3 * 1) options.
So to calculate it, we first take the person with limited choice and multiply that with the options the others still have.
-> the total number of options would be 3 * 5 * 4 * 3 * 2 * 1 = 360
(At least I'm fairly certain, as with most on this exchange, I'm a programmer rather than a mathematician)
For the suits you just subtract one person because one is already fixed.
The other 5 can each decide for one of 2 choices. This is similar to a coin flip for each person. That makes 2^5 combinations.
Then they choose the ties, where all 6 have 3 options. Following the example of the coin flip (but with 3 possible outcomes) we have 3^6 combinations for the ties.
Now just add the options together, because the decisions between suit and tie don't depend on each other. This will give you 729 outcomes for the ties and 32 outcomes for the tux's.
Hope I could make things clearer for you.
I have a large set of names (millions in number). Each of them has a first name, an optional middle name, and a lastname. I need to encode these names into a number that uniquely represents the names. The encoding should be one-one, that is a name should be associated with only one number, and a number should be associated with only one name.
What is a smart way of encoding this? I know it is easy to tag each alphabet of the name according to its position in the alphabet set (a-> 1, b->2.. and so on) and so a name like Deepa would get -> 455161, but again here I cannot make out if the '16' is really 16 or a combination of 1 and 6.
So, I am looking for a smart way of encoding the names.
Furthermore, the encoding should be such that the number of digits in the output numeral for any name should have fixed number of digits, i.e., it should be independent of the length. Is this possible?
Thanks
Abhishek S
To get the same width numbers, can't you just zero-pad on the left?
Some options:
Sort them. Count them. The 10th name is number 10.
Treat each character as a digit in a base 26 (case insensitive, no
digits) or 52 (case significant, no digits) or 36 (case insensitive
with digits) or 62 (case sensitive with digits) number. Compute the
value in an int. EG, for a name of "abc", you'd have 0 * 26^2 + 1 *
26^1 + 2 * 20^0. Sometimes Chinese names may use digits to indicate tonality.
Use a "perfect hashing" scheme: http://en.wikipedia.org/wiki/Perfect_hash_function
This one's mostly suggested in fun: use goedel numbering :). So
"abc" would be 2^0 * 3^1 * 5^2 - it's a product of powers of primes.
Factoring the number gives you back the characters. The numbers
could get quite large though.
Convert to ASCII, if you aren't already using it. Then treat each
ordinal of a character as a digit in a base-256 numbering system.
So "abc" is 0*256^2 + 1*256^1 + 2*256^0.
If you need to be able to update your list of names and numbers from time to time, #2, #4 and #5 should work. #1 and #3 would have problems. #5 is probably the most future-proofed, though you may find you need unicode at some point.
I believe you could do unicode as a variant of #5, using powers of 2^32 instead of 2^8 == 256.
What you are trying to do there is actually hashing (at least if you have a fixed number of digits). There are some good hashing algorithms with few collisions. Try out sha1 for example, that one is well tested and available for modern languages (see http://en.wikipedia.org/wiki/Sha1) -- it seems to be good enough for git, so it might work for you.
There is of course a small possibility for identical hash values for two different names, but that's always the case with hashing and can be taken care of. With sha1 and such you won't have any obvious connection between names and IDs, which can be a good or a bad thing, depending on your problem.
If you really want unique ids for sure, you will need to do something like NealB suggested, create IDs yourself and connect names and IDs in a Database (you could create them randomly and check for collisions or increment them, starting at 0000000000001 or so).
(improved answer after giving it some thought and reading the first comments)
You can use the BigInteger for encoding arbitrary strings like this:
BigInteger bi = new BigInteger("some string".getBytes());
And for getting the string back use:
String str = new String(bi.toByteArray());
I've been looking for a solution to a problem very similar to the one you proposed and this is what I came up with:
def hash_string(value):
score = 0
depth = 1
for char in value:
score += (ord(char)) * depth
depth /= 256.
return score
If you are unfamiliar with Python, here's what it does.
The score is initially 0 and the depth are set to 1
For every character add the ord value * the depth
The ord function returns the UTF-8 value (0-255) for each character
Then it's multiplied by the 'depth'.
Finally the depth is divided by 256.
Essentially, the way that it works is that the initial characters add more to the score while later characters contribute less and less. If you need an integer, multiply the end score by 2**64. Otherwise you will have a decimal value between 0-256. This encoding scheme works for binary data as well as there are only 256 possible values in a byte/char.
This method works great for smaller string values, however, for longer strings you will notice that the decimal value requires more precision than a regular double (64-bit) can provide. In Java, you can use the 'BigDecimal' and in Python use the 'decimal' module for added precision. A bonus to using this method is that the values returned are in sorted order so they can be searched 'efficiently'.
Take a look at https://en.wikipedia.org/wiki/Huffman_coding. That is the standard approach.
You can translate it, if every character (plus blank, at least) will occupy a position.
Therefore ABC, which is 1,2,3 has to be translated to
1*(2*26+1)² + 2*(53) + 3
This way, you could encode arbitrary strings, but if the length of the input isn't limited (and how should it?), you aren't guaranteed to have an upper limit for the length.
Task:
to cluster a large pool of short DNA fragments in classes that share common sub-sequence-patterns and find the consensus sequence of each class.
Pool: ca. 300 sequence fragments
8 - 20 letters per fragment
4 possible letters: a,g,t,c
each fragment is structured in three regions:
5 generic letters
8 or more positions of g's and c's
5 generic letters
(As regex that would be [gcta]{5}[gc]{8,}[gcta]{5})
Plan:
to perform a multiple alignment (i.e. withClustalW2) to find classes that share common sequences in region 2 and their consensus sequences.
Questions:
Are my fragments too short, and would it help to increase their size?
Is region 2 too homogeneous, with only two allowed letter types, for showing patterns in its sequence?
Which alternative methods or tools can you suggest for this task?
Best regards,
Simon
Yes, 300 is FAR TOO FEW considering that this is the human genome and you're essentially just looking for a particular 8-mer. There are 65,536 possible 8-mers and 3,000,000,000 unique bases in the genome (assuming you're looking at the entire genome and not just genic or coding regions). You'll find G/C containing sequences 3,000,000,000 / 65,536 * 2^8 =~ 12,000,000 times (and probably much more since the genome is full of CpG islands compared to other things). Why only choose 300?
You don't want to use regex's for this task. Just start at chromosome 1, look for the first CG or GC and extend until you get your first non-G-or-C. Then take that sequence, its context and save it (in a DB). Rinse and repeat.
For this project, Clustal may be overkill -- but I don't know your objectives so I can't be sure. If you're only interested in the GC region, then you can do some simple clustering like so:
Make a database entry for each G/C 8-mer (2^8 = 256 in all).
Take each GC-region and walk it to see which 8-mers it contains.
Tag each GC-region with the sequences it contains.
Now, for each 8-mer, you have thousands of sequences which contain it. I'll leave the analysis of the data up to your own objectives.
Your region two, with the 2 letters, may end up a bit too similar, increasing length or variability (e.g. more letters) could help.