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.
Origin | Files produced by the author(s) |
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