Summary of Large Language Model Aided Qos Prediction For Service Recommendation, by Huiying Liu et al.
Large Language Model Aided QoS Prediction for Service Recommendation
by Huiying Liu, Zekun Zhang, Honghao Li, Qilin Wu, Yiwen Zhang
First submitted to arxiv on: 5 Aug 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Distributed, Parallel, and Cluster Computing (cs.DC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A recent surge in large language model (LLM) advancements has led to their expanded use across various applications. After training on vast text corpora, LLMs can extract intricate features from textual data, making them potentially valuable for web service recommendation tasks. This paper explores the feasibility and practicality of employing LLMs for such recommendations. The proposed large language model aided QoS prediction (llmQoS) model leverages LLMs to extract relevant information from descriptive sentences describing user-service attributes. Combining this information with historical interaction data, llmQoS predicts QoS values for given user-service pairs. On the WSDream dataset, llmQoS overcomes data sparsity issues and consistently outperforms comparable baseline models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models are super smart computers that can understand lots of text. They’re getting better and better at understanding what people like about different things on the internet. This paper is all about using these language models to help recommend good matches between users and websites based on how well those sites work (QoS). The researchers created a new way to use language models to get more accurate QoS predictions, which helps fix a big problem with predicting website quality. They tested their idea on some real data and it worked really well! |
Keywords
» Artificial intelligence » Large language model
