Accuracy‐first and efficiency‐first privacy‐preserving semantic‐aware ranked searches in the cloud

Abstract

Traditional term frequency-inverse document frequency model-based privacy-preserving ranked search schemes rarely consider the latent semantic meanings of documents and keywords. It is a challenge to design efficient semantic-aware ranked search (SRSE) schemes with privacy preservation. In this paper, two privacypreserving SRSE schemes are developed for the cloud environments. The first scheme is the accuracy-first search scheme. In this scheme, the Latent Dirichlet Allocation topic model is adopted to generate the topicbased semantic information-embedded vectors for documents and queried keywords, which supports semanticaware relevance measurement. The bisecting k-means clustering algorithm is used to build an accuracy-first filtering tree index (AFF-tree), and the AFF-tree-based search algorithm is proposed to achieve the accuracy-first ranked search. The second scheme is the efficiency-first search scheme. It performs a structure optimization on the AFF-tree, and a newly efficiency-first filtering tree index (EFF-tree) is designed. By using the EFF-tree, an anchor node-based search algorithm is designed to achieve the efficiency-first ranked search at the expense of a little decrease in search result precision. The secure inner product is used to perform privacy-preserving semantic-aware relevance measurement between

Multi-strategy KOA Algorithm for Optimizing Gated Recurrent Cell Networks in Automatic Writing Scoring Method Design

“…When using machine learning models for automatic scoring, scoring feature extraction is carried out on the scoring dataset of the corresponding writing question type, and the scoring feature data obtained is used to train the original model to obtain the scoring model of the writing question type [24]. When auto-scoring, the same scoring feature extraction is performed on the text to be scored, and the obtained feature data are input to the corresponding auto-scoring model to obtain the auto-scoring results, the specific process is shown in Figure 1.…”