lexRankFromSimil {lexRankr} | R Documentation |
Compute LexRanks from pairwise sentence similarities
Description
Compute LexRanks from sentence pair similarities using the page rank algorithm or degree centrality the methods used to compute lexRank are discussed in "LexRank: Graph-based Lexical Centrality as Salience in Text Summarization."
Usage
lexRankFromSimil(s1, s2, simil, threshold = 0.2, n = 3,
returnTies = TRUE, usePageRank = TRUE, damping = 0.85,
continuous = FALSE)
Arguments
s1 |
A character vector of sentence IDs corresponding to the |
s2 |
A character vector of sentence IDs corresponding to the |
simil |
A numeric vector of similarity values that represents the similarity between the sentences represented by the IDs in |
threshold |
The minimum simil value a sentence pair must have to be represented in the graph where lexRank is calculated. |
n |
The number of sentences to return as the extractive summary. The function will return the top |
returnTies |
|
usePageRank |
|
damping |
The damping factor to be passed to page rank algorithm. Ignored if |
continuous |
|
Value
A 2 column dataframe with columns sentenceId
and value
. sentenceId
contains the ids of the top n
sentences in descending order by value
. value
contains page rank score (if usePageRank==TRUE
) or degree centrality (if usePageRank==FALSE
).
References
http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume22/erkan04a-html/erkan04a.html
Examples
lexRankFromSimil(s1=c("d1_1","d1_1","d1_2"), s2=c("d1_2","d2_1","d2_1"), simil=c(.01,.03,.5))