Abstract
A method for finding real-world associations between news topics (as distinguished from apparent associations caused by the constant size of the newspaper) is described. This is important for studying society interests.
The work was done under partial support of CONACyT, REDII, and SNI, Mexico.
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Montes-y-Gómez, M., López-López, A., Gelbukh, A. (2001). Finding Correlative Associations among News Topics. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2001. Lecture Notes in Computer Science, vol 2004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44686-9_53
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DOI: https://doi.org/10.1007/3-540-44686-9_53
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