sentenceSimil: Compute distance between sentences

In AdamSpannbauer/lexRankr: Extractive Summarization of Text with the LexRank Algorithm

Compute distance between sentences

Description

Compute distance between sentences using modified idf cosine distance from "LexRank: Graph-based Lexical Centrality as Salience in Text Summarization". Output can be used as input to lexRankFromSimil.

Usage

sentenceSimil(sentenceId, token, docId = NULL, sentencesAsDocs = FALSE)

Arguments

sentenceId	A character vector of sentence IDs corresponding to the docId and token arguments
token	A character vector of tokens corresponding to the docId and sentenceId arguments
docId	A character vector of document IDs corresponding to the sentenceId and token arguments. Can be NULL if sentencesAsDocs is TRUE.
sentencesAsDocs	TRUE or FALSE, indicating whether or not to treat sentences as documents when calculating tfidf scores. If TRUE, inverse document frequency will be calculated as inverse sentence frequency (useful for single document extractive summarization)

Value

A 3 column dataframe of pairwise distances between sentences. Columns: sent1 (sentence id), sent2 (sentence id), & dist (distance between sent1 and sent2).

References

http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume22/erkan04a-html/erkan04a.html

Examples

sentenceSimil(docId=c("d1","d1","d2","d2"),
               sentenceId=c("d1_1","d1_1","d2_1","d2_1"),
               token=c("i", "ran", "jane", "ran"))

AdamSpannbauer/lexRankr documentation built on Dec. 9, 2022, 3:44 a.m.