Queries-Based Profile Evolution using Genetic Algorithm
| Autor: | Boulkrinat Nour El Houda, Benblidia Nadjia, Meziane Abdelkrim |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Matching (statistics)
User profile Information retrieval Computer science 020204 information systems Genetic algorithm 0202 electrical engineering electronic engineering information engineering Process (computing) 020201 artificial intelligence & image processing 02 engineering and technology Recommender system |
| Zdroj: | AICCSA |
| DOI: | 10.1109/aiccsa47632.2019.9035351 |
| Popis: | User's interests are important in query reformation, filtering or recommender systems. Besides, the user profile is always dynamic due to the instability of his interests and the increase among documents. Thus, its evolution is required however identifying the changes in user's interests over time may be challenging. Recent works focused on user interests evolution, takes into account the collection by matching the document and the query or by analyzing log file of user's interactions with the system (feedbacks). However, they did not consider the queries exclusively in the evolution process. This paper proposes a new user profile evolution approach in which user's queries and interests are used to update the user profile. To do so, we use genetic algorithm technique to extract relevant interests so that to detect new interests, improve the weights of the existing ones or delete the useless among them from the profile. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|