语义丰富的地理门户搜索引擎--以ArcGIS为例
Semantically-Enriched Search Engine for Geoportals: A Case Study with ArcGIS Online
摘要：
许多地理门户网站，如ArcGIS Online的建立，以提高地理空间数据的可重用性和实现智能知识发现的目标。然而，根据以往的研究，大多数现有的地理门户网站采用基于Lucene的技术来实现其核心搜索功能，这具有有限的能力，捕捉用户的搜索意图。为了更好地理解用户的搜索意图，可以使用查询扩展来通过添加语义相似的术语来丰富用户的查询。在地理门户和地理信息检索的背景下，我们主张从地理空间和主题的角度来丰富用户的查询语义的想法。在地理空间方面，我们提出了丰富的查询，同时使用的地方partonomy和距离衰减。在主题方面，概念扩展和基于嵌入的文档相似度被用来推断隐藏在用户查询中的隐含信息。这个语义查询扩展1 2 G. Mai等人的框架被实现为一个语义丰富的搜索引擎，使用ArcGIS Online作为案例研究。构建了一个基准数据集来评估所提出的框架。我们的评估结果表明，所提出的语义查询扩展框架是非常有效的捕捉用户的搜索意图，并显着优于一个良好的建立基线Lucene的实际评分功能，在DCG@K（K= 3，5，10）的增量超过3.0。
英文摘要：
Many geoportals such as ArcGIS Online are established with the goal of improving geospatial data reusability and achieving intelligent knowledge discovery. However, according to previous research, most of the existing geoportals adopt Lucene-based techniques to achieve their core search functionality, which has a limited ability to capture the user's search intentions. To better understand a user's search intention, query expansion can be used to enrich the user's query by adding semantically similar terms. In the context of geoportals and geographic information retrieval, we advocate the idea of semantically enriching a user's query from both geospatial and thematic perspectives. In the geospatial aspect, we propose to enrich a query by using both place partonomy and distance decay. In terms of the thematic aspect, concept expansion and embedding-based document similarity are used to infer the implicit information hidden in a user's query. This semantic query expansion 1 2 G. Mai et al. framework is implemented as a semantically-enriched search engine using ArcGIS Online as a case study. A benchmark dataset is constructed to evaluate the proposed framework. Our evaluation results show that the proposed semantic query expansion framework is very effective in capturing a user's search intention and significantly outperforms a well-established baseline-Lucene's practical scoring function-with more than 3.0 increments in DCG@K (K=3,5,10).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
