Textual CBR systems solve problems by reusing experiences that are in textual form. Knowledge-rich comparison of textual cases remains an important challenge for these systems. How...
Feature selection algorithms can reduce the high dimensionality of textual cases and increase case-based task performance. However, conventional algorithms (e.g., information gain)...
Case Retrieval Networks (CRNs) facilitate flexible and efficient retrieval in Case-Based Reasoning (CBR) systems. While CRNs scale up well to handle large numbers of cases in the c...
Sutanu Chakraborti, Robert Lothian, Nirmalie Wirat...
In this paper, we present a learning framework for the semantic annotation of text documents that can be used as textual cases in case-based reasoning applications. The annotation...
In the frame of a Unified Messaging System, a crucial task of the system is to provide the user with key information on every message received, like keywords reflecting the object...