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About Popularity Modeling For Modern Apps
This document proposes a sequential approach based on hidden Markov models (HMMs) to model the popularity information of mobile apps. Specifically: 1) It introduces a popularity-based HMM (PHMM) to model sequences of heterogeneous popularity observations, including rankings, ratings, and review topics. 2) It presents a bipartite graph-based method to pre-cluster popularity observations to efficiently learn PHMM parameters and initial values. 3) It demonstrates how PHMM can be applied to mobile app services like trend-based recommendation, rating/review spam detection, and ranking fraud detection.
Detailed Information
| Author: | ['Vidya Srinivasa Kesarla'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 12 |
| Language: | English |
| Format: | |
| Price: | FREE |
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