Mining Product Experiences from User Generated Reviews: A Recommender Systems Perspective
|Title:||Mining Product Experiences from User Generated Reviews: A Recommender Systems Perspective||Authors:||Muhammad, Khalil
|Permanent link:||http://hdl.handle.net/10197/6456||Date:||Sep-2014||Abstract:||We have employed algorithms described in to mine opinions from TripAdvisor hotel reviews; we have experimented with different parameters to learn which provided more meaningful extractions. Secondly, we have considered opinion summarization and search similar to. We have implemented a retrieval strategy that accepts natural language queries based on opinions from reviews. Additionally, we have proposed various methods of summarizing opinions based on statistical metrics. Currently, we are experimenting with feature quality metrics. Our aim is to establish a relevance score that describes the usefulness of extracted opinions. We are also running recommendation experiments using different versions the extracted opinions.||Type of material:||Conference Publication||Keywords:||Recommender systems;Product descriptions||Language:||en||Status of Item:||Peer reviewed||Conference Details:||22nd International Conference on Case-Based Reasoning, Cork, Ireland, 29 September - 01 October 2014|
|Appears in Collections:||Insight Research Collection|
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