Elements of a Learning Interface for Genre Qualified Search

Even prior to content, the genre of a web document leads to a first coarse binary classification of the recall space in relevant and non-relevant documents. Thinking of a genre search engine, massive data will be available via explicit or implicit user feedback. This data can be used to improve and to customize the underlying classifiers. A taxonomy of user behaviors is applied to model different scenarios of information gain. Elements of such a learning interface, as for example the implications of the lingering time and the snippet genre recognition factor, are discussed.

• Type: Conference
• Year: 2007
• Where: AUSAI
• Authors: Andrea Stubbe, Christoph Ringlstetter, Randy Goebel
• Keywords: Artificial Intelligence, AUSAI 2007, Coarse Binary Classification, Genre Search Engine, Implicit User Feedback