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- research-articleMay 2020
Using Cognitive Models to Train Big Data Models with Small Data
AAMAS '20: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent SystemsPages 1413–1421Modeling and predicting human behavior pose a difficult challenge for AI and other related fields. Some current techniques (e.g., cognitive architectures) are able to model people's goals and actions from little data, but have poor predictive ...
- research-articleApril 2017
Temporal Effects on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation Approach
WWW '17: Proceedings of the 26th International Conference on World Wide WebPages 1401–1410https://doi.org/10.1145/3038912.3052605Hashtags have become a powerful tool in social platforms such as Twitter to categorize and search for content, and to spread short messages across members of the social network. In this paper, we study temporal hashtag usage practices in Twitter with ...
- posterOctober 2016
Model-based Reminiscence: Guiding Mental Time Travel by Cognitive Modeling
HAI '16: Proceedings of the Fourth International Conference on Human Agent InteractionPages 341–344https://doi.org/10.1145/2974804.2980492This paper proposes an approach to elderly mental care called model-based reminiscence, which utilizes cognitive modeling to guide a user's mental time travel. In this approach, a personalized cognitive model is constructed by implementing a user's ...
- short-paperApril 2014
Long time no see: the probability of reusing tags as a function of frequency and recency
WWW '14 Companion: Proceedings of the 23rd International Conference on World Wide WebPages 463–468https://doi.org/10.1145/2567948.2576934In this paper, we introduce a tag recommendation algorithm that mimics the way humans draw on items in their long-term memory. This approach uses the frequency and recency of previous tag assignments to estimate the probability of reusing a particular ...
- research-articleMarch 2008
Integrating vision and audition within a cognitive architecture to track conversations
HRI '08: Proceedings of the 3rd ACM/IEEE international conference on Human robot interactionPages 201–208https://doi.org/10.1145/1349822.1349849We describe a computational cognitive architecture for robots which we call ACT-R/E (ACT-R/Embodied). ACT-R/E is based on ACT-R [1, 2] but uses different visual, auditory, and movement modules. We describe a model that uses ACT-R/E to integrate visual ...