Estudio de algoritmos de filtrado colaborativo para sistemas recomendadores de información.
Now, the large amount of information and services products offered to users in the network makes it difficult to filter the information and find what fits the tastes and / or needs for each one. In the last 20 years, the recommender systems have become increasingly complex, trying to adjust as much...
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| Format: | bachelorThesis |
| Langue: | spa |
| Publié: |
2018
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| Accès en ligne: | http://repositorio.utc.edu.ec/handle/27000/5630 |
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Ajouter un tag | Résumé: | Now, the large amount of information and services products offered to users in the network makes it difficult to filter the information and find what fits the tastes and / or needs for each one. In the last 20 years, the recommender systems have become increasingly complex, trying to adjust as much as possible to the profile and needs of different users, giving rise to algorithms based on costly computational calculations. That is why this research provides relevant information about the structure and functioning of the collaborative algorithm and how it influences to enhance information filtering systems which presents results in some companies that automatically register the interests of users, collecting preferences or likes. For the elaboration of the present study, the qualitative research method was used. Based on this researching methodology, the aim is to explain the original scientific concept of collaborative filtering algorithms, without altering its theoretical foundation and thus allowing the reader to understand and interpret the study document. Finally, the most relevant aspects will be obtained through comparative tables, referring to the collaborative filtering algorithms. |
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