What am I gonna wear?
- 28 January 2007
- conference paper
- Published by Association for Computing Machinery (ACM)
- p. 365-368
- https://doi.org/10.1145/1216295.1216368
Abstract
Electronic Commerce on the Web is thriving, but consumers still have trouble finding products that will meet their needs and desires. AI has offered many kinds of Recommender Systems [11], but they are all oriented toward searching based on concrete attributes of the product (e.g. price, color) or the user (as in Collaborative Filtering). Based on commonsense reasoning technology, we introduce a novel recommendation technique, Scenario-Oriented Recommendation, which helps users by mapping their daily scenarios to product attributes, and works even when users don't know exactly what products they are looking for.Keywords
This publication has 9 references indexed in Scilit:
- ConceptNet — A Practical Commonsense Reasoning Tool-KitBT Technology Journal, 2004
- A model of textual affect sensing using real-world knowledgePublished by Association for Computing Machinery (ACM) ,2003
- Personal choice pointPublished by Association for Computing Machinery (ACM) ,2003
- Recommendations without user preferencesPublished by Association for Computing Machinery (ACM) ,2003
- Intelligent profiling by examplePublished by Association for Computing Machinery (ACM) ,2001
- Personalized Conversational Case-Based RecommendationLecture Notes in Computer Science, 2000
- The FindMe approach to assisted browsingIEEE Expert, 1997
- Recommender systemsCommunications of the ACM, 1997
- CYCCommunications of the ACM, 1995