Summary of A Novel Method For News Article Event-based Embedding, by Koren Ishlach et al.
A Novel Method for News Article Event-Based Embedding
by Koren Ishlach, Itzhak Ben-David, Michael Fire, Lior Rokach
First submitted to arxiv on: 20 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Social and Information Networks (cs.SI)
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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 novel lightweight method is proposed for optimizing news embedding generation, focusing on entities and themes mentioned in articles and their historical connections to specific events. The method consists of three stages: processing and extracting events, entities, and themes from news articles; generating periodic time embeddings for themes and entities using GloVe models; and concatenating article-level vectors generated by Smooth Inverse Frequency (SIF) with nuanced event-related information obtained through Siamese Neural Networks. This approach is evaluated on a dataset of over 850,000 news articles and 1,000,000 events from the GDELT project, demonstrating improved performance compared to state-of-the-art methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary News embedding is important for detecting media bias, identifying fake news, and making news recommendations. A new way to create news embeddings is proposed that focuses on entities and themes mentioned in articles and how they relate to specific events over time. This method involves three steps: extracting information from news articles, generating time-related embeddings using GloVe models, and combining these with article-level vectors generated by two different approaches. The method was tested on a large dataset of news articles and showed that it can improve performance compared to existing methods. |
Keywords
» Artificial intelligence » Embedding » Glove
