1. Workshop Co-chairs: Derek Bridge Paulo Gomes Nuno Seco Fourth Workshop in Textual Case-Based Reasoning: Beyond Retrieval

2. Session I Automatic Indexing in TCBR Session II Adaptation in TCBR Session III Maintenance & Visualization in TCBR Session IV The Workshop ChallengeFourth Workshop in Textual CBR: Beyond Retrieval

3. Session IChair: Susan Craw Automatic Indexing in TCBR Conversation for Textual Case-Based Reasoning Kalyan Gupta & David Aha Using Textual CBR for e-Learning Content Categorization & Retrieval Luis Rodrigues, Bruno Antunes, Paulo Gomes, Arnaldo Santos, Jacinta Barbeira & Rafael Carvalho Discussion Consider methods for extracting, selecting and organising features to index textual cases. To what extent are the methods domain- and task-independent? When do shallow methods suffice? When are deep methods needed? Manual methods? Highlights Definition of a new research problem: Conversational Textual CBR: how to automatically extract/organise the features that become prompts. A new methodological framework: how to evaluate this kind of feature set. (Effectiveness, efficiency. A discussion about other criteria.) A new application area: e-learning contents. Extracting features for use in solutions. Discussion of the influence of domain.

4. Session IIChair: Kalyan Gupta Adaptation in TCBR Textual CBR in jColibri: From Retrieval to Reuse Juan A. Recio-García, Belén Díaz-Agudo and Pedro A. González- Calero The Role of Natural Language Generation During Adaptation in Textual CBR Pablo Gervás, Raquel Hervás and Juan A. Recio-García Discussion Is there middle-ground between system-guided manual adaptation and full text generation? What is the right case representation in TCBR to support these different types of adaptation? Highlights A system for report authoring which guides manual adaptation of similar reports retrieved from the case base. A proposal that adaptation on structured cases can be followed by natural language generation. We discussed the practicalities of this. In the context of adaptation, we compared statistical approaches (e.g. vector space), information extraction using expert rules, and statistical approaches enhanced by learned knowledge.

5. Session IIIChair: Sarah Jane Delany Maintenance & Visualization in TCBR A Simple Approach towards Visualizing & Evaluating Complexity of Textual Case Bases Sutanu Chakraborti, Ulises Cerviño Beresi, Nirmalie Wiratunga, Stewart Massie, Robert Lothian & Stuart Watt Discussion What other kinds of visualization are needed for TCBR? Can the approach presented here be extended to these other forms? How will this guide maintenance? Highlights A simple but effective visualisation of a case base where textual cases are represented by feature vectors. An intriguing case base complexity measure: the degree to which sim. probs. have sim. solutions is assessed by the compressability of one of the visualisations. A wide-ranging discussion of the role of maintenance in TCBR and in CBR in general: “it’s not (just) about deletion”.

6. Session IVChair: Nuno Seco The Workshop Challenge Introduction to the Workshop Challenge Derek Bridge, Paulo Gomes & Nuno Seco Learning Incident Causes Amandine Orecchioni, Nirmalie Wiratunga, Stewart Massie, Sutanu Chakraborti & Rahman Mukras Finding Lexical Relations for the Reuse of Investigation Reports Luc Lamontagne, Rim Bentebibel, Erwan Miry & Sylvie Despres Discussion Led by Derek Bridge Highlights Classification of sentences in incident reports as causes or facts using a novel vector representation: separate vectors characterise subject, verb and object. Statistical techniques for recommending sentences to authors based on tools for, e.g., POS tagging, named entity extraction, construction of a translation model between problem and solution phrases... Discussion considered the merits of challenges and competitions to furthering work in TCBR, with ref. to this challenge, to the cooking competition and to TREC.

7. Thank you for your attention! Fourth Workshop in Textual Case-Based Reasoning: Beyond Retrieval