Case-Based Reasoning for Knowledge-Intensive Template Selection During Text Generation

The present paper describes a case-based reasoning solution for solving the task of selecting adequate templates for realizing messages describing actions in a given domain. This solution involves the construction of a case base from a corpus of example texts, using information from WordNet to group related verbs together. A case retrieval net is used as a memory model. A taxonomy of the concepts involved in the texts is used to compute similarity between concepts. The set of data to be converted into text acts as a query to the system. The process of solving a given query may involve several retrieval processes - to obtain a set of cases that together constitute a good solution for transcribing the data in the query as text messages - and a process of knowledge-intensive adaptation which resorts to a knowledge base to identify appropriate substitutions and completions for the concepts that appear in the cases, using the query as a source. We describe this case-based solution, and we p...

• Type: Conference
• Year: 2006
• Where: EWCBR
• Authors: Raquel Hervás, Pablo Gervás
• Keywords: Automated Reasoning, Case Retrieval Net, Case-based Reasoning Solution, EWCBR 2006, Messages Describing Actions