Academic resource recommendation service system and method

Abstract

The invention provides an academic resource recommendation service system and method. The method comprises the following steps: crawling academic resources on an internet by using an LDA (Latent Dirichlet Allocation)-based focused crawler, classifying the academic resources according to preset A types by using an LDA-based text classification model, and storing the academic resources in a local academic resource database, wherein the system further comprises an academic resource model, a resource quality value calculation module and a user interest module; implanting a tracking software module at a user terminal, combining interesting subjects and historical browsing behavior data of the user, respectively modeling the academic resource model and the user interest module by virtue of four dimensions such as the academic resource type, subject theme distribution, key word distribution and LDA latent theme distribution, calculating the similarity between the academic resource model and the user interest preference module, combining the resource quality value to calculate the recommendation degree, and finally perform academic resource Top-N recommendation for the user according to the recommendation degree. According to the method disclosed by the invention, personalized accurate recommendation of the academic resources is performed according to the identity, interest and browsing behaviors of users, and the working efficiency of scientific research personnel is improved.

Description

technical field [0001] The invention relates to the field of computer application technology, in particular to an academic resource recommendation service system and a method for providing academic resource recommendation services to related users by using the resource recommendation service system. Background technique [0002] At present, we have entered the era of big data, especially in the field of academic resources, where hundreds of millions of various academic resources are generated every year. In addition to academic papers and patents, there are also a large number of academic resources such as academic conferences, academic news, and academic community information emerging in real time. These types of academic resources are of great significance for users to accurately and efficiently grasp the current scientific research status in fields of interest. However, scientific research users usually have heavy scientific research work. This kind of academic resources ...

AI Technical Summary

Problems solved by technology

[0005] In addition, with the discovery of the Internet, the Internet is filled with a large number of information texts in various forms such as news, blogs, and meeting minutes. Such information texts more or less include academic-related information, and often include the latest Academic research information is concerned by people of various related disciplines, and this kind of information text is messy and disorderly, often with overlapping disciplines, and generally does not have classification information itself. It is often difficult to make correct automatic classification of this type of information text in the existing technology. It is difficult for people in various related disciplines to use traditional search engines to find out and accurately search, and the search process is also cumbersome. Users often need to spend a lot of time and energy when searching for academic resources they are interested in, which affects their work efficiency.

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