Internet of Things search has great potential applications with the rapid development of Internet of Things technology. Combining Internet of Things technology and academic search to build academic search framework based on Internet of Things is an effective solution to realize massive academic resource search. Recently, the academic big data has been characterized by a large number of types and spanning many fields. The traditional web search technology is no longer suitable for the search environment of academic big data. Thus, this paper designs academic search framework based on Internet of Things Technology. In order to alleviate the pressure of the cloud server processing massive academic big data, the edge server is introduced to clean and remove the redundancy of the data to form a clean data for further analysis and processing by the cloud server. Edge computing network effectively makes up for the deficiency of cloud computing in the conditions of distributed and high concurrent access, reduces long-distance data transmission, and improves the quality of network user experience. For Academic Search, this paper proposes a novel weakly supervised academic search model based on knowledge-enhanced feature representation. The proposed model can relieve high cost of acquisition of manually labeled data by obtaining a lot of pseudolabeled data and consider word-level interactive matching and sentence-level semantic matching for more accurate matching in the process of academic search. The experimental result on academic datasets demonstrate that the performance of the proposed model is much better than that of the existing methods.

中文翻译：

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基于知识增强特征表示的弱监督学术搜索模型

随着物联网技术的飞速发展，物联网搜索具有巨大的应用潜力。结合物联网技术和学术搜索，构建基于物联网的学术搜索框架，是实现海量学术资源搜索的有效解决方案。近年来，学术大数据呈现出种类多、跨领域多的特点。传统的网络搜索技术已不再适合学术大数据的搜索环境。因此，本文设计了基于物联网技术的学术搜索框架。为了缓解云服务器处理海量学术大数据的压力，引入边缘服务器对数据的冗余进行清理和去除，形成干净的数据，供云服务器进一步分析处理。边缘计算网络有效弥补了云计算在分布式、高并发访问条件下的不足，减少了远距离数据传输，提高了网络用户体验质量。对于学术搜索，本文提出了一种基于知识增强特征表示的新型弱监督学术搜索模型。该模型可以通过获取大量伪标记数据来缓解人工标记数据获取的高成本，并在学术搜索过程中考虑词级交互匹配和句子级语义匹配以实现更准确的匹配。