Pith. sign in

REVIEW 2 cited by

Variations of the Similarity Function of TextRank for Automated Summarization

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1602.03606 v1 pith:V2RHA4NC submitted 2016-02-11 cs.CL cs.IR

Federico Barrios , Federico López , Luis Argerich , Rosa Wachenchauzer This is my paper · ORCID
classification cs.CLcs.IR
keywords algorithmfunctionsimilaritysummarizationtextrankachievealternativesarticle
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

This article presents new alternatives to the similarity function for the TextRank algorithm for automatic summarization of texts. We describe the generalities of the algorithm and the different functions we propose. Some of these variants achieve a significative improvement using the same metrics and dataset as the original publication.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Generative Retrieval for Book search

    cs.IR 2025-01 conditional novelty 5.0 of 10

    GBS applies generative retrieval to book search by augmenting training data with hierarchical book identifiers and pseudo-queries, and encoding books with outline-based bi-level positions and retentive attention, repo...

  2. Investigating Corporate Social Responsibility Initiatives: Examining the case of corporate Covid-19 response

    cs.IR 2025-02 conditional novelty 4.0 of 10

    Topic modeling and text summarization of 15 Nasdaq firms' Covid-19 press releases shows CSR messaging shifting from employee safety and operations toward community help, testing, and student learning by mid-2020.

Pith tools