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Individualized recommending method and system based on element path

A recommendation method and meta-path technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problem of ignoring the recommendation effect, and achieve the effect of increasing novelty and diversity and improving accuracy

Inactive Publication Date: 2014-07-30
南京大学镇江高新技术研究院
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AI Technical Summary

Problems solved by technology

Traditional recommendation systems often only focus on the target item type information, while ignoring the improvement of other item type information on the recommendation effect. For example, in a movie recommendation system, users may like the movie adapted from the novel because of their favorite novel; It may also be because of a movie starring a singer you like

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  • Individualized recommending method and system based on element path
  • Individualized recommending method and system based on element path
  • Individualized recommending method and system based on element path

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Embodiment Construction

[0035] The invention provides a meta-path-based personalized recommendation method and system. A detailed description will be given below in conjunction with the accompanying drawings.

[0036] refer to figure 1 , figure 1 It is a flow chart of the steps of the meta-path-based personalized recommendation method of the present invention, including the following steps:

[0037] Information acquisition step 101: Obtain the user's historical behavior information on the item, the social relationship between users and the attribute information of the item itself;

[0038] Constructing a heterogeneous network directed graph Step 102: constructing a heterogeneous network directed graph containing node types based on all the obtained information;

[0039] Building a summary graph step 103: constructing a summary graph based on the node types in the directed graph of the heterogeneous network and the relationship between node types;

[0040] Meta-path acquisition step 104: Based on th...

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Abstract

The invention discloses an individualized recommending method and system based on an element path. The recommending method comprises the following steps: building a heterogeneous network graph through collecting article content information, social relationship among users and user historical behavior information; utilizing a relevance measurement method based on heterogeneous bi-directional random walk to measure the preference degrees of a user on articles based on semantics; utilizing machine learning to synthesize the preference degrees of the user under different semantics and predict the preference degrees of the user on unselected articles so as to recommend favorable articles to the user. According to the system, the accuracy, novelty and diversity of the recommending effect are effectively improved through comprehensively utilizing the additive information of other article types to a target article type based on the content, cooperation filtering and the social network relationship and digging the semantic features of the information.

Description

technical field [0001] The invention relates to a meta-path-based personalized recommendation method and system, and belongs to the technical field of data mining and machine learning. Background technique [0002] With the vigorous development of Web2.0 technology and social network, more and more information has entered people's daily life. Faced with massive information, it is becoming more and more difficult for people to obtain valuable information from it. For this reason, recommendation systems aiming at helping users easily obtain useful information from massive amounts of information are playing an increasingly important role in people's daily life. The recommendation system is mainly based on the user's personal information and historical behavior on items, analyzes user preferences, and tracks changes in user interests, so as to recommend relevant information of interest to users, eliminating the trouble of users searching for information. Mainstream recommender ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 高春华叶保留陆桑璐
Owner 南京大学镇江高新技术研究院
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