论文标题
信息检索的概念嵌入
Concept Embedding for Information Retrieval
论文作者
论文摘要
概念用于解决术语不匹配的问题。但是，我们需要概念之间有效的相似性度量。单词嵌入提供了一个有希望的解决方案。我们在这项研究中介绍了三种基于单词向量的概念向量的方法。我们使用基于向量的度量来估计概念间相似性。我们的实验显示出令人鼓舞的结果。此外，单词和概念变得可比。这可以用于改善概念索引过程。
Concepts are used to solve the term-mismatch problem. However, we need an effective similarity measure between concepts. Word embedding presents a promising solution. We present in this study three approaches to build concepts vectors based on words vectors. We use a vector-based measure to estimate inter-concepts similarity. Our experiments show promising results. Furthermore, words and concepts become comparable. This could be used to improve conceptual indexing process.
