發(fā)布時(shí)間：2018-05-19 22:21

  本文選題：個(gè)性化 + 推薦�。� 參考：《圖書情報(bào)工作》2017年S1期

【摘要】：為解決當(dāng)前個(gè)性化推薦不能同時(shí)考慮用戶興趣點(diǎn)受時(shí)間和頻率兩個(gè)維度共同影響問題,提出一種基于本體相似度和時(shí)間衰減的動態(tài)個(gè)性化推薦算法。首先確定時(shí)間衰減函數(shù)來計(jì)算用戶興趣點(diǎn)的時(shí)間衰減規(guī)律,然后考慮不同興趣點(diǎn)訪問頻率對興趣點(diǎn)關(guān)注程度的影響,再次通過本體相似的綜合算法解算推薦資源與關(guān)注目標(biāo)資源的相似度,最后通過興趣點(diǎn)更新權(quán)重與相似度的加成效果確定推薦資源的排序。實(shí)驗(yàn)結(jié)果表明該算法在整體上具有較好的綜合性能,推薦資源的查準(zhǔn)率和查全率均較高,算法的普適性和效果較好。
[Abstract]:A dynamic personalized recommendation algorithm based on ontology similarity and time attenuation is proposed to solve the problem that users' interest points can not be affected by both time and frequency dimensions. First, the time attenuation function is determined to calculate the time decay law of the user's point of interest, and then the influence of different access frequency of the point of interest on the interest degree is considered. Thirdly, the similarity between the recommended resources and the target resources is calculated by the ontology similarity synthesis algorithm. Finally, the order of the recommended resources is determined by the addition effect of updating the weights and similarity of the points of interest. The experimental results show that the algorithm has better comprehensive performance on the whole, the recall rate and recall rate of recommended resources are both higher, and the universality and effect of the algorithm are better.
【作者單位】： 云南財(cái)經(jīng)大學(xué)科研院所黨委;
【基金】：國家自然科學(xué)基金“綜合交通體系下邊境口岸物流均衡智能方法研究”(項(xiàng)目編號:61163035)研究成果之一
【分類號】：G252;TP391.3

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本文編號：1911942