2021Journal of Physics Conference SeriesOpen access

An improved model of document retrieval efficiency based on information theory

Xiaoli Li, Yin Xiaokai, Kan Li

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Abstract

Abstract Literature retrieval is an important auxiliary work of scientific research. The form of literature retrieval is becoming more and more abundant, the number of literature is huge, and the storage set is complex. The algorithm of retrieval tools directly affects the accuracy and efficiency of retrieval. Based on the analysis of the problems existing in various literature retrieval technologies, an improved TF-IDF literature retrieval efficiency model is proposed. It provides a new idea for the design and implementation of literature retrieval system.

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What this paper is about

Abstract Literature retrieval is an important auxiliary work of scientific research. The form of literature retrieval is becoming more and more abundant, the number of literature is huge, and the storage set is complex. The algorithm of retrieval tools directly affects the accuracy and efficiency of retrieval. Based on the analysis of the problems existing in various literature retrieval technologies, an improved TF-IDF literature retrieval efficiency model is proposed. It provides a new idea for the design and implementation of literature retrieval system.

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Available abstract

Abstract Literature retrieval is an important auxiliary work of scientific research. The form of literature retrieval is becoming more and more abundant, the number of literature is huge, and the storage set is complex. The algorithm of retrieval tools directly affects the accuracy and efficiency of retrieval. Based on the analysis of the problems existing in various literature retrieval technologies, an improved TF-IDF literature retrieval efficiency model is proposed. It provides a new idea for the design and implementation of literature retrieval system.

Key concepts: Computer science, Information retrieval, Data retrieval, Human–computer information retrieval, Vector space model, Document retrieval, Set (abstract data type), Data mining

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