| 张晓宇.基于浏览记录挖掘的个性化偏好建模[J].高技术通讯(中文),2013,23(9):933~938 |
| 基于浏览记录挖掘的个性化偏好建模 |
| Personalized preference modeling based on browsing history mining |
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| DOI： |
| 中文关键词: 个性化检索，偏好建模，浏览记录挖掘，用户体验，相关反馈 |
| 英文关键词: personalized retrieval,preference modeling,browsing history mining,user experience,relevance feedback |
| 基金项目: |
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| 摘要点击次数: 3165 |
| 全文下载次数: 2705 |
| 中文摘要: |
| 为提高个性化信息检索性能，提出了一种基于浏览记录挖掘的偏好建模算法。该算法从浏览记录出发，深入挖掘用户在域和域值这两个维度上的偏好，从而自动构建并累积更新偏好模型，对检索结果进行个性化优化；给定查询，相关结果能够自动根据现有浏览记录进行偏好建模以实现个性化排序，无需任何额外的用户操作。讨论了关键参数的优化，以进一步提升算法性能，使其更加符合实际应用的需求，从而在精确刻画用户偏好的同时有效提升了用户体验。实验结果表明，基于浏览记录挖掘的个性化偏好建模算法能够显著提高检索性能，对于海量信息的有效获取具有重要意 |
| 英文摘要: |
| A novel preference modeling algorithm based on browsing history mining is proposed to improve the personalized retrieval performance of informafion retrieval systems.Based on the browsing log,the algorithm deeply explores users’ interest in both the dimensions of field and field value,and automatically constructs and accumulatively updates the preference model to optimize the personalized retrieval.Given a query,the relevant retrieval results can spontaneously be ranked according to their corresponding preference score without any extra user interference.Advanced settings are subsequently discussed to further improve the algorithm for practical use.The experimental results demonstrate the advantages of the proposed algorithm over the previous work. |
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