Name: Modeling Activation Processes in Human Memory for Tag Recommendations (en Inglés)
SKU: 57532003
Price: 101010.00 CLP
Availability: InStock
Author: Kowald, Dominik
ISBN: 9786202320726

portada Modeling Activation Processes in Human Memory for Tag Recommendations (en Inglés)

Modeling Activation Processes in Human Memory for Tag Recommendations (en Inglés)

Formato

Libro Físico

Autor

Dominik Kowald

Editorial

Sudwestdeutscher Verlag Fur Hochschulschrifte

Idioma

Inglés

N° páginas

168

Encuadernación

Tapa Blanda

Dimensiones

22.9x15.2x1 cm

Peso

0.25 kg.

ISBN13

9786202320726

Categorías

Tecnología de la información: cuestiones generales

Modeling Activation Processes in Human Memory for Tag Recommendations (en Inglés)

Dominik Kowald (Autor) · Sudwestdeutscher Verlag Fur Hochschulschrifte · Tapa Blanda

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Reseña del libro "Modeling Activation Processes in Human Memory for Tag Recommendations (en Inglés)"

Social tagging systems enable users to collaboratively assign freely chosen keywords (i.e., tags) to resources (e.g., Web links). In order to support users in finding descriptive tags, tag recommendation algorithms have been proposed. One issue of current state-of-the-art tag recommendation algorithms is that they are often designed in a purely data-driven way and thus, lack a thorough understanding of the cognitive processes that play a role when people assign tags to resources. A prominent example is the activation equation of the cognitive architecture ACT-R, which formalizes activation processes in human memory to determine if a specific memory unit (e.g., a word or tag) will be needed in a specific context. It is the aim of this thesis to investigate if a cognitive-inspired approach, which models activation processes in human memory, can improve tag recommendations. The findings of this thesis demonstrate that activation processes in human memory can be utilized to improve not only social tag recommendations but also hashtag recommendations. This opens up a number of possible research strands for future work, such as the design of cognitive-inspired recommender systems.