ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Techniques and Knowledge Used for Adaptation During Case-Based Problem Solving
IEA/AIE '98 Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial In telligence and Expert Systems: Tasks and Methods in Applied Artificial Intelligence
The Knowledge Engineering Review
Building CBR systems with jcolibri
Science of Computer Programming
Semantics and Experience in the Future Web
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Case Retrieval Reuse Net (CR2N): An Architecture for Reuse of Textual Solutions
ICCBR '09 Proceedings of the 8th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
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Textual reuse is an integral part of textual case-based reasoning (TCBR) which deals with solving new problems by reusing previous similar problem-solving experiences documented as text. We investigate the role of text reuse for text authoring applications that involve feedback or review generation. Generally providing feedback in the form of assigning a rating from a likert scale is far easier compared to articulating explanatory feedback as text. When previous feedback generated about the same or similar objects are maintained as cases, there is opportunity for knowledge reuse. In this paper, we show how compositional and transformational adaptation techniques can be applied once sentences in a given case are aligned to relevant structured attribute values. Three text reuse algorithms are introduced and evaluated on a dataset gathered from online Hotel reviews from TripAdvisor. Here cases consists of both structured sub-rating attributes together with textual feedback. Generally, aligned sentences linked to similar sub-rating values are clustered together and prototypical sentences are then extracted to enable reuse across similar authors. Experiments show a close similarity between our proposed texts and actual human edited review text. We also found that problems with variability in vocabulary are best addressed when prototypes are formulated from larger sets of similar sentences in contrast to smaller sets from local neighbourhoods.