Depending on user profiles expressed by associated expected events, and conditions for raising alerts, from manual meticulous news annotation of an adequately selected corpus, an ontology domain is created. A cross-language information retrieval approach is used for automatic translation of financial documents corresponding to the particular domain corresponding to the user requirement. By this way, users may receive alerts and news expressed in their own language even if they are initially expressed in a different language. Manual annotation is used for knowledge extraction composed of general rules useful for automatic annotation of financial news arriving instantly to the system from reliable providers of information. As a first step in the loop, news are filtered, split into different sub-documents each one corresponding to a particular event and categorized. News are then mapped automatically to formatted data as instantiations of a sequence of predefined entities defined an event. By using alerting conditions given by the user, data analysis of structured tables might raise or not alerts to the user, with an adequate explanation of the cause of the alert. Automatically selected alerts initiate a new process for information generation to the user by starting a new browsing sequence of news containing events which are related to the raised alerts. Related news are recursively processed through the same structuring process in order to offer more historical data related to the alert helping the user to make decision.


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  1. A.M. Jaoua, N. Semmar, H. Essafi, S. Elloumi, J. Al'Jaam, H. Hammami, F. Laban, F. Ferjani, A multilingual financial watch alerting system, QFARF Proceedings, 2010, CSP17.
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