Product-Based Neural Networks for User Response Prediction
Shanghai Jiao Tong University · University College London · +1 more institution
Abstract
Predicting user responses, such as clicks and conversions, is of great importance and has found its usage inmany Web applications including recommender systems, websearch and online advertising. The data in those applicationsis mostly categorical and contains multiple fields, a typicalrepresentation is to transform it into a high-dimensional sparsebinary feature representation via one-hot encoding. Facing withthe extreme sparsity, traditional models may limit their capacityof mining shallow patterns from the data, i.e. low-order featurecombinations. Deep models like deep neural networks, on theother hand, cannot be directly applied for the high-dimensionalinput because of the huge feature space. In this paper,…
Citation impact
- FWCI
- 57.28
- Percentile
- 100%
- References
- 31
Authors
7Topics & keywords
- Categorical variable
- Computer science
- Feature (linguistics)
- Product (mathematics)
- Artificial neural network
- Representation (politics)
- Recommender system
- Artificial intelligence