semantics

I know that for a list, partial matching is done when indexing using the basic operators $ and [[ . For example: ll <- list(yy=1) ll$y [1] 1 But I am still an R newbie and this is new for me, partial matching of function arguments: h <- function(xx=2)xx h(x=2) [1] 2 I want to understand how this works. What is the mechanism behind it? Does this have any side effects? I want understand how can someone test if the xx argument was given? Edit after Andrie comment: Internally R uses pmatch algorithm to match argument, here an example how this works: pmatch("me", c("mean", "median", "mode")) #

Are both <h1><a ...> ... </a></h1> and <a ...><h1> ... </h1></a> valid HTML, or is only one correct? If they are both correct, do they differ in meaning? Marco Both versions are correct. The biggest difference between them is that in the case of <h1><a>..</a></h1> only the text in the title will be clickable. If you put the <a> around the <h1> and the css display property is block (which it is by default) the entire block (the height of the <h1> and 100% of the width of the container the <h1> resides in) will be clickable. Historically you could not put a block element inside of an inline

Is there a difference between these two statements inside a function? bool returnValue = true; //Code that does something return(returnValue); and this? bool returnValue = true; //Code return returnValue; The former has parentheses around returnValue . Michael Petch As of C++14, they often are. C++14 adds a fringe case where parentheses around a return value may alter the semantics. This code snippet shows two functions being declared. The only difference is parentheses around the return value. int var1 = 42; decltype(auto) func1() { return var1; } // return type is int, same as decltype(var1)

input: phrase 1, phrase 2 output: semantic similarity value (between 0 and 1), or the probability these two phrases are talking about the same thing Matt Mower You might want to check out this paper: Sentence similarity based on semantic nets and corpus statistics (PDF) I've implemented the algorithm described. Our context was very general (effectively any two English sentences) and we found the approach taken was too slow and the results, while promising, not good enough (or likely to be so without considerable, extra, effort). You don't give a lot of context so I can't necessarily recommend