景点，标题和标签:挖掘世界各地的照片数据库观光

Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics Pub Date : 2020-06-30 DOI:10.1145/3405962.3405987

A. Luberg, Jakob Pindis, T. Tammet

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引用次数: 0

摘要

本文的重点是计算合适的地名和描述标签的大型照片集合的视觉上有趣的景点。分析的核心数据集包含4500万张来自Panoramio数据库的地理标记图片。我们提出了几种分析方法以及用于标签推荐的机器学习实验，并基于对照片标题中最广泛使用的标签词及其受欢迎程度的分析，提出了一种手动构建的标签分类方法。所采用的方法、选定的标签和分类可用于为视觉上有趣的景点构建不同的旅游应用程序。

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Sights, titles and tags: mining a worldwide photo database for sightseeing

The paper focuses on calculating suitable place names and descriptive tags for large photo collections of visually interesting sights. The core dataset analyzed contains 45 million crowd-sourced geotagged pictures of the Panoramio database. We present several methods for analysis along with machine learning experiments for tag recommendation and suggest a manually built taxonomy of tag categories, based on the analysis of most widely used taglike words in the photo titles, along with their popularities. The methods, selected tags and the taxonomy can be used for building different tourism applications for visually interesting sights.

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Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics

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