A Measuring Method for User Similarity based on Interest Topic
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Summary
This article argues a similarity measure method that based on user’s interest topic division is argued that gets the highest @ P N and sorting accuracy compared with the traditional tag-based user similarity.
- Type
- article
- Published
- 2018-04-01
- Cited by
- 1
- References
- 15
- Access
- Open access
- OpenAlex
- https://openalex.org/W2801837171
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:145047525
Keywords
Similarity (geometry), Computer science, Data mining, Information retrieval, Artificial intelligence
References
- Collaborative filtering recommender systems based on popular tags
- Tag-Based User Profiling for Social Media Recommendation
- Collaborative filtering based on collaborative tagging for enhancing the quality of recommendation
- Tag-aware recommender systems by fusion of collaborative filtering algorithms
- Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemsitry
- Web 2.0 social bookmark selection for tag clustering
- A Survey of Collaborative Filtering Techniques
- HT06, tagging paper, taxonomy, Flickr, academic article, to read
- Tagsplanations: explaining recommendations using tags
- Topic-sensitive PageRank
- Automatic Clustering of Social Tag using Community Detection
- Exploring folksonomy for personalized search
- A social tag clustering method based on common co-occurrence group similarity
- Topic-sensitive PageRank
- TagClusters: Semantic Aggregation of Collaborative Tags beyond TagClouds
- Personalizing Navigation in Folksonomies Using Hierarchical Tag Clustering
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