† In this paper, we compare two methods for article summarization. The first method is mainly based on term-frequency, while the second method is based on ontology. We build an o...
Major media companies such as The Financial Times, the Wall Street Journal or Reuters generate huge amounts of textual news data on a daily basis. Mining frequent patterns in this...
We consider layouting news articles on a page as a cutting and packing problem with output maximization. We propose to tailor news articles by employing automatic summarization to...
Temporal Text Mining (TTM) is concerned with discovering temporal patterns in text information collected over time. Since most text information bears some time stamps, TTM has man...
In this manuscript we present the summarization and categorization subsystems of a complete mechanism that begins with web-page fetching and concludes with representation of the c...