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Blog Author Information Dataset
Art & Digital Creations
Tags and Keywords
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"No reviews yet"
Free
About
This dataset provides essential metadata related to authors, primarily designed to enhance blog recommendation systems. It serves as a foundational resource for developing and studying algorithms that deliver personalised and engaging user experiences by presenting relevant content to readers [1]. By analysing user behaviour and preferences, recommendation algorithms can adapt to individual interests over time, improving the accuracy and relevance of their suggestions [1]. The dataset facilitates the exploration of various recommender paradigms, including collaborative filtering, which identifies user similarities, content-based filtering, which relies on item attributes, and hybrid algorithms that combine both approaches [1]. Understanding these complexities can lead to more effective recommendation system development [1].
Columns
The dataset includes the following columns:
- author_id: A unique identifier for each author [2].
- author_name: The name of the author [2].
Distribution
The data typically comes in a CSV file format [3]. The dataset features 6,868 unique author IDs, indicating a substantial number of distinct authors [2]. Specific numbers for the total rows or records are not explicitly available, but the presence of many unique author IDs suggests a dataset of considerable size. The dataset is listed as Version 1.0 and has a high quality rating of 5 out of 5 [4].
Usage
This dataset is ideal for:
- Developing and evaluating blog recommendation systems that provide tailored content suggestions [1].
- Researching and implementing various recommender algorithms, such as collaborative, content-based, or hybrid models [1].
- Analysing user behaviour and preferences to improve content delivery and engagement [1].
- Gaining deeper insights into the complexities of recommendation systems and their effective leverage [1].
- Creating personalised and engaging digital experiences for readers [1].
Coverage
The dataset has a global regional coverage [4]. Specific time ranges or demographic scopes for the authors or their content are not detailed within the provided sources. The dataset was listed on 21st June 2025 [4].
License
CC0
Who Can Use It
This dataset is particularly useful for:
- Data Scientists and Machine Learning Engineers: To build, test, and refine content recommendation algorithms [1].
- Researchers: To study the application and effectiveness of different recommender paradigms in the context of online content [1].
- Content Platforms and Publishers: To implement personalised content experiences for their readers [1].
- Developers: To integrate sophisticated recommendation features into applications and services [1].
Dataset Name Suggestions
- Blog Author Metadata
- Author Data for Recommendation Systems
- Blog Author Information
- Content Author Directory
Attributes
Original Data Source: Blog Recommendation Data
QUALITY