Context recommendation method and device based on high-order singular value decomposition

A high-order singular value and singular value decomposition technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problem of not clearly specifying the central tensor dimension, coarse granularity, and affecting the accuracy of calculation results, To achieve the effect of fine granularity, high calculation accuracy, and improved accuracy

Active Publication Date: 2018-09-21
GUANGDONG MECHANICAL & ELECTRICAL COLLEGE
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Problems solved by technology

In the process of using high-order singular value decomposition, the selection of the central tensor dimension and the calculation of the context weight are the key factors to determine the accuracy of the algorithm, but the previous method did not clearly indicate how to determine the central tensor dimension, and when calculating the context weight When the granularity is too coarse, it affects the accuracy of the calculation results

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  • Context recommendation method and device based on high-order singular value decomposition
  • Context recommendation method and device based on high-order singular value decomposition
  • Context recommendation method and device based on high-order singular value decomposition

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Embodiment 1

[0061] Such as figure 1 As shown, it is a system architecture diagram of the present embodiment, including two parts: the context information collection and processing part, and the recommendation engine part; figure 2As shown, it is a schematic diagram of the context information collection and processing part of this embodiment. First, the GPS positioning information is obtained from the user's mobile device, and then according to the time and location information, the weather information is obtained by using a third-party database; , Weather information is preprocessed, for example, for the "time" context, 6 to 12 am is defined as morning, represented by 1, 12 to 14 is defined as noon, represented by 2, and 14 to 18 is defined as afternoon, represented by 3 Indicates that 18:00 to 24:00 is defined as evening, represented by 4, and from 24:00 to 6:00 of the next day is defined as early morning, represented by 5. Here, different division rules may be adopted according to spe...

Embodiment 2

[0111] Such as Figure 9 As shown, it is the context recommendation device based on high-order singular value decomposition of this embodiment, which includes an information acquisition module, a first building module, a replacement module, an expansion module, a second building module, a calculation module, a third building module and Generate modules, the specific functions of each module are as follows:

[0112] The information obtaining module is used to obtain user's rating information on items and corresponding context information.

[0113] The first building block is configured to build a third-order tensor corresponding to each context according to different context types.

[0114] The replacement module is used for constructing a third-order tensor corresponding to each context, if a user has rated an item multiple times in the same context, the average value is used for replacement.

[0115] The expansion module is used to expand each third-order tensor according t...

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Abstract

The invention discloses a context recommendation method and device based on high-order singular value decomposition. The method comprises the steps of obtaining grading information of a user on a project and corresponding context information; constructing a three-order tensor corresponding to each piece of context according to different context types; expanding each three-order tensor according toan expansion rule to obtain three second-order matrices; according to all the second-order matrices, determining a central tensor dimension by utilizing the singular value decomposition, and constructing a new third-order tensor; calculating the weight of each piece of context; constructing an N-order tensor according to the new third-order tensor and the corresponding context weights; finding the position corresponding to the target user on the N-order tensor according to a target user ID and a project ID, and generating a recommendation list for the target user. By means of the method, thecontext information is fused into recommendation generation, and by calculating the context weights and determining the central tensor dimension, the accuracy of a recommendation result is greatly improved.

Description

technical field [0001] The present invention relates to a context recommendation method and device, in particular to a context recommendation method and device based on high-order singular value decomposition, belonging to the field of information recommendation. Background technique [0002] With the rapid development of the Internet, people have entered the era of information overload. As one of the effective means to alleviate "information overload", the recommendation system uses the existing selection process or similar relationship to mine potential interest objects of each user. In many scenarios, such as when the user is in a mobile environment, the user's preference is affected by contextual factors such as location, weather, time, etc. The context-aware recommendation system can further improve the accuracy of the recommendation by introducing context into the recommendation. [0003] At present, some experts and scholars have proposed to introduce the high-order ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 熊冬青李家春
Owner GUANGDONG MECHANICAL & ELECTRICAL COLLEGE
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