Serendipity Movie Test Data

<b>Serendipity Movie Test Data</b> The serendipity relatedness problem consists of, given an entity, to find another entity that is serendipitously related to it. The strategy adopted consists of diving the dataset in partitions based in a global feature, genre, and linking entities from different partitions according to connectivity criteria. This dataset supports the evaluation of approaches that address the serendipity relatedness problem. It covers the movie domain and uses data available in DBpedia and LinkedMDB, which are popular reference linked data datasets for this domain. The dataset contains 404 entities of the movies domain split in 15 cinematographic genres. For every entity, the dataset contains: (1) its linked data URIs; (2) its linked data datagraph, encompassing the network of entities that surrounds it; (3) a list of serendipitously suggested movies. And for every entity pair, the dataset contains: (1) the linked data paths that connect the pair; (2) a score according to the extracted paths. The data is compressed in .zip format and can be uncompressed by standard compression utilities. The data are split into two archives: <b>dataset.zip:</b> contains raw data (.json, .ttl). The underlying data and code can be accessed through standard text edit software.

<b>意外关联电影测试数据集（Serendipity Movie Test Data）</b>
意外关联性问题（serendipity relatedness）的定义为：给定一个实体（entity），寻找另一个与之存在意外关联关系的实体。本数据集采用的构建策略为：基于全局特征——影片类型（genre）将数据集划分为多个分区，并依据连通性准则连接不同分区中的实体。本数据集可用于评估针对意外关联性问题的各类解决方案，覆盖电影领域，所用数据源自该领域主流的参考级关联开放数据数据集DBpedia与LinkedMDB。
本数据集包含电影领域的404个实体，被划分为15个电影类型分区。针对每个实体，数据集提供以下内容：(1) 其关联开放数据统一资源标识符（linked data URIs）；(2) 其关联开放数据数据图（linked data datagraph），涵盖其周边的实体关联网络；(3) 一份意外推荐影片列表。针对每一对实体，数据集包含以下内容：(1) 连接该实体对的关联开放数据路径；(2) 基于提取路径计算得到的关联得分。
本数据集以.zip格式压缩，可通过标准解压工具进行解压。数据分为两个归档文件：<b>dataset.zip:</b> 包含原始数据（.json、.ttl格式）。底层数据与代码可通过标准文本编辑软件读取与编辑。