Analyzing and Comparing On-Line News Sources via (Two-Layer) Incremental Clustering

Abstract : In this paper, we analyse the contents of the web site of two Italian news agencies and of four of the most popular Italian newspapers, in order to answer questions such as what are the most relevant news, what is the average life of news, and how much different are different sites. To this aim, we have developed a web-based application which hourly collects the articles in the main column of the six web sites, implements an incremental clustering algorithm for grouping the articles into news, and finally allows the user to see the answer to the above questions. We have also designed and implemented a two-layer modification of the incremental clustering algorithm and executed some preliminary experimental evaluation of this modification: it turns out that the two-layer clustering is extremely efficient in terms of time performances, and it has quite good performances in terms of precision and recall.
Document type :
Conference papers
Complete list of metadatas

Cited literature [10 references]  Display  Hide  Download

https://hal.inria.fr/hal-01390139
Contributor : Marie-France Sagot <>
Submitted on : Thursday, November 10, 2016 - 8:48:02 AM
Last modification on : Wednesday, August 21, 2019 - 9:02:02 PM
Long-term archiving on : Wednesday, March 15, 2017 - 2:54:54 AM

File

AnalyzingAndComparing.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Francesco Cambi, Pierluigi Crescenzi, Linda Pagli. Analyzing and Comparing On-Line News Sources via (Two-Layer) Incremental Clustering. 8th International Conference on Fun with Algorithms, FUN 2016, Jun 2016, La Maddalena, Italy. ⟨10.4230/LIPIcs.FUN.2016.9⟩. ⟨hal-01390139⟩

Share

Metrics

Record views

224

Files downloads

248