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一個基于用戶畫像的商品推薦算法的設計與應用

發表時間:2018-02-28? 瀏覽量:2535? 下載量:504
全部作者: 呂超,朱鄭州
作者單位: 北京大學軟件與微電子學院
摘 要: 以用戶畫像的商品推薦為研究背景,在真實的電商環境下,使用海量數據構建用戶畫像和商品畫像。對畫像數據進行詳細探討,并針對不同的優化目標對訓練目標中使用的標簽數據進行區分和說明,實現了一個線上欄目的商品推薦算法。詳細闡明用戶畫像和商品畫像的構建方案,以說明關聯用戶和商品交互信息的標簽數據的獲取。定義分別以銷量和點擊率為優化目標,并分別給出了這兩種優化目標的不同標簽構建方案和實現方法。在構建用戶畫像、商品畫像和標簽數據后,詳細說明特征構建的過程;在構建特征數據和優化目標后,詳細闡明基于機器學習中梯度提升決策樹的模型訓練過程和參數調整方案得到的分數預測模型。最后利用訓練好的分數預測模型、新用戶列表和推薦的商品召回列表進行商品推薦。在完成商品推薦算法的設計和實現后,對模型進行應用和驗證。研究結果證實,本文算法相比人工排序能獲得更好的結果。
關 鍵 詞: 計算機應用;用戶畫像;電子商務;梯度提升決策樹;推薦算法
Title: Design and application of a commodity recommendation algorithm based on user portrait
Author: Lü Chao, ZHU Zhengzhou
Organization: School of Software & Microelectronics, Peking University
Abstract: Based on the user portrait of the commodity recommendation as the research background, in the real electricity supplier environment, massive data is used to build user portrait and commodity portrait. With detailed discussion on the portrait data, the used label data of the training target for different optimization goals are distinguished and described, then an online column recommendation algorithm is implemented. This paper expounds the construction scheme of the user portrait and commodity portrait, and then explains the acquisition of the tag data of the interactive user and commodity interactive information. This paper defines the optimization target of sales volume and click rate respectively, and gives the different label construction schemes and realization methods of these two optimization targets. After the construction of user portrait, commodity portrait and tag data, the process of characteristics construction is described in detail. After the construction of characteristics data and the optimization goal, the score prediction model is elaborated based on the model training process and parameter adjustment method of gradient boosted decision tree in machine learning. Finally, the training score prediction model, new user list and recommended commodity recall list are used for commodity recommendation in this paper. After completing the design and implementation of the commodity recommendation algorithm, the model is applied and verified. The results show that the algorithm in this paper can get better results than the manual sorting.
Key words: computer applications; user portrait; E-commerce; gradient boosted decision tree; recommendation algorithm
發表期數: 2018年2月第4期
引用格式: 呂超,朱鄭州. 一個基于用戶畫像的商品推薦算法的設計與應用[J]. 中國科技論文在線精品論文,2018,11(4):339-347.
 
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