Information Recommendation Research Based On Associated Data

In this era of information explosion,a large number of messages make it really difficult for internet users to search information that is valuable to them,resulting in low utilization of messages and increasing cost of information collection.Nowaday,the search engine and the recommendation system are to facilitate the users to filter "useless" data,however,due to the lack of srpport of semantic information,the current recommendation system for information retrieval methods are not perfect,which also leads to high recall and low precision.Linked-data is the best practice of the Semantic Web,as a new data representation,shared access and multiplexing integration of ideas and models.Starting from the perspective of the Semantic Web,Linked-data emphasizes the Resource Description Framework(RDF)and Uniform Resource Identifiers(URI)for the data service semantic description providing semantic support for the machine to identify and understand,while helping the units connected in the network from file refining the resource data and relational data file,greatly reducing the data sharing and reusing difficulties.The introduction of Linked-data in information recommendation could bring about change for recommennding information.Compared with the traditional way of information recommendation,recommendtion based on the information Linked-data more accurately realizes the information needs of users,based on semantic and associated data,recommends or provides more accurate information.This paper starts from the concept of Linked-data and information recommendation,studies the information recommendation and traditional information recommendation method based on Linked-data to find different analysis of deficiency of traditional information recommendation method and the influence of Linked-data in information recommendation,introduces the realization and management of Linked-data and information recommendation models.In the fifth chapter,the author verifies the feasibility and innovation of information.recommendation based on Linked-data basing on the Linked-data to construct a recommendation system based on the information associated with the data.