Title :
From computational intelligence to Web intelligence
Author :
Cercone, Nick ; Hou, Lijun ; Keselj, Vlado ; An, Aijun ; Naruedomkul, Kanlaya ; Hu, Xiaohua
Author_Institution :
Dalhousie Univ., Halifax, NS, Canada
fDate :
11/1/2002 12:00:00 AM
Abstract :
The authors explore three topics in computational intelligence: machine translation, machine learning and user interface design and speculate on their effects on Web intelligence. Systems that can communicate naturally and learn from interactions will power Web intelligence´s long term success. The large number of problems requiring Web-specific solutions demand a sustained and complementary effort to advance fundamental machine-learning research and incorporate a learning component into every Internet interaction. Traditional forms of machine translation either translate poorly, require resources that grow exponentially with the number of languages translated, or simplify language excessively. Recent success in statistical, nonlinguistic, and hybrid machine translation suggests that systems based on these technologies can achieve better results with a large annotated language corpus. Adapting existing computational intelligence solutions, when appropriate for Web intelligence applications, must incorporate a robust notion of learning that will scale to the Web, adapt to individual user requirements, and personalize interfaces.
Keywords :
Internet; information resources; language translation; learning (artificial intelligence); natural language interfaces; Internet; Web intelligence; World Wide Web; computational intelligence; large annotated language corpus; machine learning; machine translation; natural language; user interface design; Competitive intelligence; Computational intelligence; Intelligent systems; Internet; Learning systems; Machine learning; Metasearch; Natural languages; Relational databases; Search engines;
DOI :
10.1109/MC.2002.1046978