Multi-dimensional Aggregation Recommendation Algorithm Based on Average Prediction

Traditional collaborative filtering recommendation algorithm uses single dimensional data to calculate the similarity between users or items, ignoring the user’s preference, thus affect the recommendation accuracy. To this end, an averaging forecasting based multi-dimensional aggregation recommendat...

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Main Authors:	Han Jiaxin, Wei Wenjuan, Xia Haiyang
Format:	Article
Language:	English
Published:	EDP Sciences 2018-01-01
Series:	MATEC Web of Conferences
Online Access:	https://doi.org/10.1051/matecconf/201817303043

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spelling	doaj-87d66d5ef7f24a06a3b0aac15fea6ebe2021-02-02T04:01:28ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-011730304310.1051/matecconf/201817303043matecconf_smima2018_03043Multi-dimensional Aggregation Recommendation Algorithm Based on Average PredictionHan JiaxinWei WenjuanXia HaiyangTraditional collaborative filtering recommendation algorithm uses single dimensional data to calculate the similarity between users or items, ignoring the user’s preference, thus affect the recommendation accuracy. To this end, an averaging forecasting based multi-dimensional aggregation recommendation algorithm was proposed in this paper, which constructs the relationship aggregation function by user’s total score and dimension scores firstly, then apply the aggregation function to the initial multi-dimensional score that calculated by the modified averaging forecasting algorithm. The experiment result shows that compared with the previous collaborative filtering based recommendation algorithm, it has higher recommendation accuracy.https://doi.org/10.1051/matecconf/201817303043
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Han Jiaxin Wei Wenjuan Xia Haiyang
spellingShingle	Han Jiaxin Wei Wenjuan Xia Haiyang Multi-dimensional Aggregation Recommendation Algorithm Based on Average Prediction MATEC Web of Conferences
author_facet	Han Jiaxin Wei Wenjuan Xia Haiyang
author_sort	Han Jiaxin
title	Multi-dimensional Aggregation Recommendation Algorithm Based on Average Prediction
title_short	Multi-dimensional Aggregation Recommendation Algorithm Based on Average Prediction
title_full	Multi-dimensional Aggregation Recommendation Algorithm Based on Average Prediction
title_fullStr	Multi-dimensional Aggregation Recommendation Algorithm Based on Average Prediction
title_full_unstemmed	Multi-dimensional Aggregation Recommendation Algorithm Based on Average Prediction
title_sort	multi-dimensional aggregation recommendation algorithm based on average prediction
publisher	EDP Sciences
series	MATEC Web of Conferences
issn	2261-236X
publishDate	2018-01-01
description	Traditional collaborative filtering recommendation algorithm uses single dimensional data to calculate the similarity between users or items, ignoring the user’s preference, thus affect the recommendation accuracy. To this end, an averaging forecasting based multi-dimensional aggregation recommendation algorithm was proposed in this paper, which constructs the relationship aggregation function by user’s total score and dimension scores firstly, then apply the aggregation function to the initial multi-dimensional score that calculated by the modified averaging forecasting algorithm. The experiment result shows that compared with the previous collaborative filtering based recommendation algorithm, it has higher recommendation accuracy.
url	https://doi.org/10.1051/matecconf/201817303043
work_keys_str_mv	AT hanjiaxin multidimensionalaggregationrecommendationalgorithmbasedonaverageprediction AT weiwenjuan multidimensionalaggregationrecommendationalgorithmbasedonaverageprediction AT xiahaiyang multidimensionalaggregationrecommendationalgorithmbasedonaverageprediction
_version_	1724306690630746112

Multi-dimensional Aggregation Recommendation Algorithm Based on Average Prediction

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