A personalized stock investors alert system

Jameela Al-Jaroodi, Nader Mohamed

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)


    Stock investors all agree that one of the hardest things they have to do is keep up with the rapid changes in the markets. The Internet carries a huge amount of up-to-the minute information for investors such as current stock prices, exchange rates, sales volumes, latest deals, trading averages, organizations' performance and financial information, oil and other goods prices, and much more. Although such stock-related information is publicly and freely available on the Internet, investors face difficulties tracking the changes and updates fast enough to make sound investment decisions. This paper proposes a system to monitor stock and other stock-related information available from web services or dynamic HTML documents on the Internet. This system can deal with public information available on the Internet on a single or multiple websites and from a single or multiple web services as the information sources. The system allows investors to use these sources to create personalized stock monitoring criteria and then receive updated notifications from the system based on the specified criteria. The public information is treated as a set of Internet variables used to define stock monitoring criteria based on the specific investor's requirements. Based on the defined criteria, SMS and/or email notification messages can be generated and sent to the investor notifying him/her whenever the criteria are met. A number of applications related to stock investments can benefit form this system to provide real-time useful information to the investors.

    Original languageEnglish
    Pages (from-to)875-882
    Number of pages8
    JournalJournal of Software
    Issue number8
    Publication statusPublished - 2009


    • Information retrieval
    • Notification systems
    • Stock investors
    • Web alerts
    • Web information

    ASJC Scopus subject areas

    • Software
    • Human-Computer Interaction
    • Artificial Intelligence


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